Today, we're releasing AI Talent Rediscovery for Plus and Enterprise customers. It surfaces the most qualified candidates already in your Ashby database for any open role by using AI to understand criteria rather than relying on keyword matching.

https://www.loom.com/share/80c8be6a35ec4bb9a723cab65a0fe3f9

For most recruiting teams, when a new role opens, the immediate instinct is to start sourcing from scratch, even when candidates who nearly made it to an offer, or who interviewed well for a different role six months ago, are already in the system.

The problem isn't that those candidates don't exist. It's that finding them is time-intensive, requires manual search and review, and misses anyone who described their experience differently than the job description expects. 

### **How AI Talent Rediscovery works**

AI Talent Rediscovery evaluates candidates in your database against the criteria you define for a job, just like you would in AI-assisted application review. Instead of scanning for exact words, the AI reads resumes the way a recruiter would: it understands experience, infers relevance, and assesses fit against must-haves, should-haves, and nice-to-haves.

If you've already built out your job criteria, you have what you need to run a search.

![](https://a-us.storyblok.com/f/1017310/3440x2160/64060a64a7/aitr-setup.png)

### **Refreshing stale profiles**

Candidate profiles can be incomplete or out of date if someone applied months or years ago. AI Talent Rediscovery includes automatic data refresh for any returned candidates: when available, it retrieves updated work history, location and education so evaluations stay accurate even when the original resume is sparse or outdated. This runs automatically and is performed on returned candidates at no additional cost.

### **Candidate signals and prioritized buckets**

High-fit candidates can have different histories. Some are silver medalists, while others applied when a hire was already close. Having that context helps frame the review, reduces cognitive load, and speeds up your team's decision-making.

AI Talent Rediscovery surfaces behavioral signals for each candidate based on stage progression, scorecard ratings, email thread analysis, and AI classification. It then groups candidates into prioritized buckets so you know where to start.

![](https://a-us.storyblok.com/f/1017310/3440x2160/b519c30e1a/aitr-prioritization.png)


By default, AI Talent Rediscovery shows positive signals in priority order:

- **Warm Lead:** expressed interest through a sourcing form or hiring event but never interviewed
- **Silver Medalist:** reached an active interview stage with only positive feedback and 50%+ criteria match
- **High Fit Candidates:** 75%+ criteria match, progressed past screening, and no poor interview performance
- **Re-Visit Overlooked:** 75%+ criteria match but only reached pre-interview screen
- **Promising Leads to Re-Engage:** 50%+ criteria match, progressed past screening, and didn't ghost
- **Internal Transfers:** hired for a different role, judged suitable for this one by AI, and 50%+ criteria match
- **Review Later / Dismissed:** your own curated lists

It filters out negative signals, including Recently Rejected (within the last six months), Poor Fit, Poor Interview Performance, and Candidate Ghosted. The ghosting signal only applies when a candidate does not respond to non-automated outreach. Automated emails like NPS surveys never count against them.

A simple way to start is to begin with the highest priority bucket and work downward, spending time in each bucket until you stop finding strong candidates.


### **Reviewing candidates and calibrating with hiring managers**

Clicking into any candidate opens a review panel with everything you need to decide whether to move them forward:

- The candidate's resume
- A criteria evaluation breakdown showing which requirements they meet and by what percentage
- A summary of their behavioral signals, full application history, and any previous scorecard feedback

Keyboard navigation lets you move through candidates quickly without leaving the panel.

![](https://a-us.storyblok.com/f/1017310/3440x2160/735f5dd6b2/aitr-candidate-view.png)

This workflow is especially useful for early-stage calibration with a hiring manager. Instead of debating an ideal candidate profile in the abstract, you can pull up real profiles in Rediscovery and use the criteria breakdown to pressure-test requirements. Add strong candidates to Review Later to build a shortlist in minutes.

### **Taking action**

From the review panel, you can take direct action on any candidate: add them to a sequence, consider them for the role, add them to a project, or dismiss them. Bulk actions are also available for each of these for teams working through larger result sets.

![](https://a-us.storyblok.com/f/1017310/2446x1098/2b8cffbce7/bulk-action-2-aitr.jpeg)


### **AI-personalized re-engagement outreach**

Re-engaging past candidates is different from cold sourcing. To do it well, you need to acknowledge the prior relationship, reference specific context, and explain why this role is a match.

AI Talent Rediscovery adds a re-engagement token you can use in sequence templates. When you send a sequence, the AI drafts personalized copy based on the candidate's Ashby history, including prior applications, interview notes, feedback, and past communications. You review and approve the draft before anything is sent.

You can also set a default Rediscovery sequence template at the org level to make the review-to-send process faster. Because the candidate's history lives in Ashby, the context needed to write a relevant, specific outreach message is already there.

![](https://a-us.storyblok.com/f/1017310/1851x1533/e93150abdd/sequence.png)

### **Release and pricing details**

AI Talent Rediscovery is available to customers on Plus and Enterprise plans. Pricing is 1 credit per candidate returned in your results, capped at 250 credits per search. You're only charged for candidates that appear in your buckets. Recently rejected candidates, poor fits, and candidates you've already acted on are excluded before credits are counted.

### **Getting started**

To enable AI Talent Rediscovery for your organization, go to Admin > Organization Settings > Opt-In Features and toggle on "Talent Rediscovery." To enable it on a job, go to the job's criteria section and turn on AI Talent Rediscovery. Once active, the Rediscovery tab will appear on the job.

For best results, start with a complete set of job criteria before running a search. The quality of AI matching is directly tied to the specificity of your criteria.

Visit our [help article](https://docs.ashbyhq.com/ai-talent-rediscovery) for more details, or book a demo to see how AI Talent Rediscovery can help your team fill roles faster by re-engaging the best candidates already in your database.

Use AI to scan your existing candidates, match them against job criteria, and surface key signals for rediscovery.

Introducing AI Talent Rediscovery in Ashby to surface your strongest past candidates

AI talent rediscovery

Today, we're releasing Ashby Assistant in Slack in open beta for all customers. Now, you can DM the Ashby app in Slack to ask questions about candidates, jobs, interviews, and feedback. Take actions like drafting emails, advancing candidates, or adding notes, without opening Ashby.

https://www.loom.com/share/43fe3d7ecbed401ab5800ad79af669df

This saves time for recruiters and hiring managers by reducing context switching and copy-paste, while keeping the same permissions and review steps as Ashby.

### Why we're bringing Ashby Assistant into Slack

Slack is where many hiring conversations happen. Hiring managers use Slack to message recruiters about candidates, run debrief threads, and make approvals. But when it's time to take action, like submit feedback, advance a candidate, or get a report, you've had to leave Slack and open Ashby.

Ashby Assistant in Slack is the same assistant we just launched inside Ashby, with full conversational parity, and the convenience of being able to access it in Slack. 

![](https://a-us.storyblok.com/f/1017310/3440x2160/91e37ce438/assistant-in-slack-overview.png)

### Have a 1:1 conversation with Ashby Assistant from DM

To use it, DM the Ashby app in Slack. Each new DM starts a new conversation, and replies within a thread keep full context from earlier messages in that thread. You can ask a question, refine the prompt, switch topics, and follow up within the thread. The experience is a private DM and 1:1 with the Ashby app.

![](https://a-us.storyblok.com/f/1017310/3440x2160/f64de40ad1/assistant-in-slack-feedback.png)

At any point, you can open Ashby Assistant in the web app and continue the conversation there.

The Slack assistant runs on the full set of tools available in the web app. You can ask it to look up a candidate, search your candidate pool, pull up an interview plan, find a job posting, or run a broad search across your Ashby data, with linked citations back to Ashby.

### See a preview of the action before it happens

When the assistant is about to take an action, like sending an email, changing an application stage, or adding a note, it renders a preview in Slack with Confirm and Reject buttons, and the user gives final approval. 

![](https://a-us.storyblok.com/f/1017310/2420x2058/3fb69968ba/assistant-in-slack-3.jpeg)

- For an email, you'll see a card with To, From, Subject, and the full body, plus a Send button.
- For a stage change, you'll see the candidate name, the job, and the current and target stages, plus a Change Stage button.
- For a note, you'll see the candidate name, the note content, and your avatar.
- For a form fill, you'll see a card with the form content and a Submit or Close button.
- If a preview cannot render cleanly for a particular action, the assistant falls back to a text-based confirmation with Approve and Reject options.

![](https://a-us.storyblok.com/f/1017310/3440x2160/0d150425ad/assistant-in-slack-form.png)

Every Ashby action you take from Slack still gets the equivalent review step you'd get in the web app.

### Use Custom Agents from Ashby Assistant

The Custom Agents you build in Ashby Assistant are available in Slack. To use a custom agent in Slack, describe it by name in your message, for example: "Using the debrief agent, can you brief me on Simon Patel?" The assistant selects the right agent, runs it, and returns the result back into the thread.

![](https://a-us.storyblok.com/f/1017310/1413x1763/6fd8927f7d/assistant-in-slack-2.png)

Note: you can't @mention agents directly in Slack the way you can in the web app, but referring to them by name in your message works the same way.

### Permissions and access

Each Slack user maps to a single Ashby user. Every action and every piece of data the assistant accesses runs on behalf of that user, with the same permissions they already have in Ashby. If a user couldn't see a candidate's private notes in the web app, they can't see them through Slack either.

Access works the way it does in Ashby, so teams do not need to change how permissions are managed.

### Release and pricing details

Ashby Assistant in Slack is available today as an open beta for all customers. It is free during  testing period. Once we move to general availability, it will draw from your existing allotment of AI Credits, including when used through Slack.

### Getting started

If you already have the Ashby Slack app installed and Ashby Assistant is turned on for your organization, you are ready to get started. Open a DM with the Ashby app to prompt Ashby Assistant. 

If you have not set up the Slack integration yet, you can install it from the Integrations section of your admin settings. If you need to set up Ashby Assistant, you can turn it on from the Admin Settings under Opt-In Features. 

Visit our [help center](https://docs.ashbyhq.com/using-ashby-agents-in-slack) for setup details, or book a demo to see it in action.

Use Ashby Assistant right where you work in Slack. Ask questions, submit feedback, call custom agents, and more directly from Slack.

Use Ashby Assistant directly in Slack

Ashby Assistant in Slack

Recruiting teams carry a lot of context: candidate sentiment across a pipeline, interview feedback on a long-open role, notes from a debrief that inform an offer. That context lives in Ashby, but pulling it together often means navigating across profiles, scrolling through feedback forms, and piecing it together across tabs.

**Today, we're releasing Ashby Assistant**, a chat-based agent that lets you ask questions in plain language and take action across Ashby from a single interface. 

Ashby Assistant is available in open beta with opt-in access. 

https://www.loom.com/share/3c9024bf9f5942ac9b8dedf8cb67538e

### Ask Ashby anything across your hiring data

The assistant has access to your candidates, interview plans, jobs, applications, interviews, feedback forms, and interview transcripts. Your existing Ashby permissions apply, so it can only read and act on information you can already access.

For example, you can ask for a pipeline update on an open Product Engineer role that includes candidate sentiment, current stage, and concerns raised in interviews. Every answer includes citations back to the underlying data in Ashby, so you can trace each claim and click through to the source.

![](https://a-us.storyblok.com/f/1017310/3440x2160/6493f30be7/pipeline-update.png)

You can ask follow-up questions in the same conversation to dig deeper or refine a result.

### Take action directly from the chat

Ashby Assistant can also take action on your behalf. From the same conversation, you can ask it to:

- Draft and send a candidate email
- Add a note to a candidate profile
- Advance a candidate to the next stage
- Consider a candidate for a job
- Create a new candidate
- Fill out a form

Every action prompts you for review before it runs. If you ask for an offer congratulations email that references a candidate's feedback highlights, you'll see the full draft with the option to refine, regenerate, or confirm before anything is sent.

![](https://a-us.storyblok.com/f/1017310/1000x733/1b72fb09ce/gif-agent.gif)

### Build Custom Agents for repeatable work

Great prompts take time to get right, and often need more context than you want to rewrite every time. Custom agents let you capture that work once and reuse it. To create a custom agent, click "New agent" in the Ashby Assistant interface, then build from scratch or start from a template. 
![](https://a-us.storyblok.com/f/1017310/1776x1398/baa0b9b03f/custom-agent-templates.jpeg)

Write plain-language instructions that define its goal, what inputs it should ask for, which sources it should use, how to format outputs, and what actions it's allowed to take. Once saved, run it by @mentioning it in any chat or selecting it from your agent list.

![](https://a-us.storyblok.com/f/1017310/3440x2160/479f22b805/create-a-custom-agent.png)

If you want every candidate debrief to check against your team's operating principles, you can build that format once in a custom agent and reuse it whenever you need it.

![](https://a-us.storyblok.com/f/1017310/1782x1166/6b36005039/debrief-agent-in-menu.png)


### Share agents across your organization

Personal agents are for your own work, like capturing how you like to draft a particular type of email.

Shared agents are for workflows you want consistent across the team, like a debrief format every hiring manager uses.

Org admins can designate an agent as shared when saving it, or convert an existing personal agent into a shared agent. Org admins can also edit shared agents at any time. Visibility is role-based, so the right teams see the right tools.

![](https://a-us.storyblok.com/f/1017310/2542x1318/03f8842b32/shared-agents.jpeg)


### Permissions and citations

All agent actions run as the user, so every read and write respects that user's existing job, team, and object-level permissions. An agent can't help someone see or change something they couldn't already access in Ashby. Elevated access users and org admins can create and use agents; limited access users cannot. Every response includes citations back to the underlying records in Ashby.

### Release and pricing details

Ashby Assistant and custom agents are available today as an opt-in open beta for all customers. They are free during the beta period. Once generally available, they will consume your existing allotment of AI Credits.

### Getting started

To turn it on, go to Admin and enable Ashby Assistant in your opt-in settings. Once enabled, you'll see "Ashby AI" in the top menu. Visit our [help center](https://docs.ashbyhq.com/ashby-agents) for more details, or book a demo to see it in action.

A chat-based agent that lets you ask questions in plain language and take action across Ashby from a single interface. Analyze pipelines, update candidates, draft emails, and more, with custom agents for repeated workflows.

AI agents with full context of your Ashby data that can act on your behalf

Ashby Assistant

We're introducing formula fields and field comparison filters in Ashby, bringing custom calculations and field-to-field comparisons into your reports, dashboards, offer forms, and approval workflows.

https://www.loom.com/share/86cc409afcbe4667aa0e757143a96c5b

This release includes three features:

- **General formula fields**: Create custom formulas saved as reusable fields across all reporting 
- **Offer formula fields**: Auto-calculate values on the offer form using formulas
- **Field comparison filters**: Compare one field against another field's value in any filter

## General formula fields

Your team wants to track and report on metrics that don't exist as standard fields or must be custom calculations - compa ratios, time-to-hire variants, custom efficiency metrics. 

General formula fields, available for Enterprise customers, let you build these calculations directly in Ashby and save them as reusable fields across your reporting.

![](https://a-us.storyblok.com/f/1017310/1832x1638/614d602901/general-formula-field-compa-ratio.png)


For example, a compa ratio field that divides salary by the midpoint of the comp range. Pull it into a report and you can immediately see where each offer stands relative to the band, helping your team make informed comp decisions across roles and departments.

![](https://a-us.storyblok.com/f/1017310/1672x1340/188f42bad2/general-formula-field-editor.png)

To build a field like compa ratio, head to the new formula editor. It supports mathematical, logical, and date functions, and you can use fields from any subject- candidates, offers, openings, interviews - and the resulting field works wherever you'd use any other field.

Other examples include custom time-to-hire calculations (application date to offer start date, measured in days) or derived metrics that combine multiple fields into a single reportable value.

Define a calculation once and it's available to your entire team across reports and dashboards.

## Field comparison filters

Field comparison filters let you compare one field against another field's value in any filter.

Standard filters compare a field to a static value you set. Field comparisons evaluate the relationship between two fields dynamically based on each record's data.

**Example**: you want to surface every offer where salary landed outside the approved compensation band. Every opening has a different range, so filtering by a fixed dollar amount doesn't work well. 

![](https://a-us.storyblok.com/f/1017310/2388x1070/4208396d9c/comparison-field-filter.png)

With field comparison filters, you filter salary against the opening's compensation range and every out-of-band offer surfaces immediately.

This, of course, works beyond just currency fields. 

![](https://a-us.storyblok.com/f/1017310/2782x1564/755cb2b473/hm-interviewer-load-dept-comparison-field-filter.png)


Compare an interviewer against the job's hiring manager to understand interview load by department, or identify interviews where the candidate's referrer is the same person conducting the interview.

Field comparison filters work anywhere there's filtering - reports, approvals, automations, alerts - get started by finding the search icon in your filters when setting a value.

Available on Plus and Enterprise plans.

## Offer formula fields

Offer formula fields auto-calculate values directly on the offer form using the same formula editor. Below, we see a simple bonus calculation. 

![](https://a-us.storyblok.com/f/1017310/2286x1426/c450e52045/offer-formula-fields.png)

Any field available to offers can be used as an input to a formula, and derived fields populate and update in real time as your team fills in the form. You also have the option to lock this value if needed. 

Common use cases are things like total compensation calculations, bonus derivations, hourly salary equivalents, or any custom calculation your offer process requires.

![](https://a-us.storyblok.com/f/1017310/2678x1482/1993300237/offer-formula-fields.png)

This is useful for any team looking to standardize derived values on their offers, ensuring everyone sending out offers is calculating the right values without any manual effort.

You can easily see when an offer field is configured with a default field. 
![](https://a-us.storyblok.com/f/1017310/1714x1176/304e80d0e9/offer-formula-field-indicator.png)

We'll also give the option to override (and reset) the default calculated field if needed. 

![](https://a-us.storyblok.com/f/1017310/800x576/aa20b8b5b1/override-formula-fields.gif)

Available on Plus and Enterprise.

## Getting Started

The calculations your team runs regularly - comp analysis, time-to-hire breakdowns, process validation - can now live inside Ashby where the rest of your hiring data already is. Every formula you build is immediately available to anyone on your team, in any report or dashboard, without a spreadsheet in between.

General formula fields are available on Enterprise. You can head over to calculated fields in admin to get started.

![](https://a-us.storyblok.com/f/1017310/2866x1566/29a9eabd4c/calculated-fields-setup.png)

Offer formula fields are available on Plus and Enterprise. Set them up where you manage custom offer fields. 

![](https://a-us.storyblok.com/f/1017310/2336x1466/3b64481be8/custom-offer-fields-formula.png)

Field comparison filters are available on Plus and Enterprise and you'll notice a new icon to select a field instead of a static value on your filters. 

![](https://a-us.storyblok.com/f/1017310/2838x1514/f0426a6116/select-field.png)

If you want to learn more about these features you can head over to our knowledge base to learn more:  
- [General Formula Fields](https://docs.ashbyhq.com/formula-fields)
- [Offer Formula Fields](https://docs.ashbyhq.com/offer-formula-fields) 
- [Field Comparison Filters](https://docs.ashbyhq.com/field-comparison-filters) 

You can also [book a demo](https://www.ashbyhq.com/request-demo) to see these features in action. 


We're introducing formula fields and field comparison filters in Ashby, bringing custom calculations and field-to-field comparisons into your reports, dashboards, offer forms, and approval workflows.

Build custom calculations in your reports and compare fields for filtering

Build Custom Calculations in your reports and Compare Fields to Filter

We're introducing AI Report Interpretations, giving you one-click access to summaries and key insights for reports in Ashby.

https://www.loom.com/share/72677f8f1a7e4c66b2dd7d4180ba03e8

We've been investing in making reports easier to create and access across Ashby, from [AI report building](https://www.ashbyhq.com/product-updates/ai-assisted-report-builder) and job dashboards to [core dashboards](https://www.ashbyhq.com/product-updates/core-dashboards) and our [redesigned reporting UI](https://www.ashbyhq.com/product-updates/simplified-report-builder). 

As more users build and interact with reports, our next task is to help you better comprehend your analytics and quickly answer "what should I take away from this report?" so that you can move from insight to decision-making much faster. 

AI Report Interpretations build on our reporting foundation to provide a concise summary of a report's configuration alongside generated insights, so you can easily confirm what a report covers to understand and communicate key takeaways to your stakeholders.

## How it works

### Explain report

![](https://a-us.storyblok.com/f/1017310/2818x1410/4047253093/1-explain-report.png)

On your reports, you'll see a new "Explain Report" button in the "Interpretation" panel. When you click it, two things happen:

![](https://a-us.storyblok.com/f/1017310/1906x1434/a181e00f71/2-summary-insights.png)


1. **A high-level summary** describes what the report is showing: the subject, time frame, filters, groupings, and visualization type.


2. **AI-generated insights** highlight notable patterns in the data, giving you a starting point for analysis across any report. Each insight references specific data points and can be expanded for detail and copied for sharing.

![](https://a-us.storyblok.com/f/1017310/2262x1396/38babc70c9/2-5-talent-trends-benchmarks.png)


Where relevant, some insights will link directly to related [Talent Trends](https://www.ashbyhq.com/talent-trends-report) benchmark reports helping you ground your data to industry benchmarks.

### AI-Assisted titles and notes

In addition to report interpretation, we're also adding AI-assisted generation for report titles and notes. The report note field now supports AI autofill, helping you create clear, descriptive summaries that make reports easier for others to understand at a glance. 

![](https://a-us.storyblok.com/f/1017310/2058x1258/3e26775ba2/3-ai-autofill.png)

Report titles also support AI generation, so giving a report an accurate and useful name takes less effort.

![](https://a-us.storyblok.com/f/1017310/2094x1394/f78b8d37c6/report-title-generation.png)


If you're building a report library that your team or hiring managers can self-serve from, clear titles and descriptions go a long way. AI-assisted generation helps you maintain that clarity in a consistent way, especially as the number of reports and dashboards you manage grows.

### Dashboard Experience

AI Report Interpretations work on dashboards too. Each report tile on a dashboard has a new "Explain Report" option, so you can run an interpretation directly from the dashboard context.

![](https://a-us.storyblok.com/f/1017310/2358x1420/9a3e85c1a9/4-dashboard-view.png)


When you're reviewing a dashboard before a leadership sync or a weekly team check-in, knowing the exact scope of each report matters. 

![](https://a-us.storyblok.com/f/1017310/2370x1466/458979f3b5/5-dashbboard-view.png)

The interpretation reflects any filters applied, so you can confirm what you're looking at before presenting it. For example: "This time to offer by recruiter report is filtered to Engineering and Product departments, located in APAC."

## Elevating report comprehension across your team

**For anyone building or managing reports**, these AI-powered report interpretations help communicate the filters, groupings, and timeframe of the reports you're building to newcomers and audiences that may not be intimately familiar with your reports.

**For anyone reviewing or presenting reports**, the insights give you ready-made talking points for stakeholder reviews or team syncs. They surface patterns like which source channels are underperforming, where application volume dropped, or which departments have diverse archive reasons, so you can walk into any conversation with specifics.

**For teams sharing dashboards broadly**, AI-generated Notes and clear titles help hiring managers and executives self-serve from dashboards. A hiring manager checking where their open roles stand, or a VP reviewing hiring health across departments, can read the note and interpretation to understand what the report covers without asking someone to walk them through it.

AI Report Interpretations add a meaningful comprehension layer helping everyone on your team understand and act on what they're seeing.

Open your reports and look for the "Explain Report" button in the interpretation panel, or try it from any report tile on a dashboard. You can learn more about this feature by heading to our [knowledge base article](https://docs.ashbyhq.com/ai-report-interpretation) or by [booking a demo](https://www.ashbyhq.com/request-demo) to see it in action.

We're introducing AI Report Interpretations, giving you one-click access to a plain-language summary and key insights for reports in Ashby.


AI-powered report interpretations for clear, actionable insights

AI Report Interpretations to help you comprehend and communicate report insights

Today, we're releasing AI Notetaker, in public beta, to support your interviewing workflows. AI Notetaker will automatically record, transcribe, and summarize your interviews while providing AI-powered assistance to help drive faster, more confident hiring decisions.

![](https://a-us.storyblok.com/f/1017310/1005x587/2992029ac3/ai-notetaker-hero.png)

Trying to take notes during an interview while staying present has long been a challenge for interviewers. 

Interviews are a critical point of contact during the hiring process and any time you're not able to connect with candidates is a missed opportunity to conduct a high-touch moment. 

But, interviews are also time-intensive so you need to ensure you're capturing all the right details to support a hiring decision. 

Third-party AI notetakers were developed to solve this but brought along additional admin overhead, scattered candidate data, multiple AI vendor terms, and limits to how many interviewers could actually leverage the tool. 

Let's take a look at how AI Notetaker in Ashby helps you fully engage with candidates while streamlining your post-interview workflow. 

### Automatically record, transcribe, and summarize your meetings

![](https://a-us.storyblok.com/f/1017310/2880x1576/18ffd11307/join-meeting.png)

AI Notetaker can be configured to automatically join your interviews as a participant. After a meeting, the recording and transcript will appear on the associated interview briefing right next to where your feedback submissions take place.
![](https://a-us.storyblok.com/f/1017310/1125x707/75a7115f97/ai-notetaker-transcript.png)

From here you have access to several tools in the interview briefing to help your team in their post-interview workflows. We'll automatically generate summary notes based on the transcription pulling out key themes and relevant details. This helps give interviewers a structured, consistent, analysis of the call. 

![](https://a-us.storyblok.com/f/1017310/1036x706/a6ab60353e/ai-notetaker-notes.png)

Everything in the notes summary has reference links so you can see the surrounding context from the interview as needed. 

> "Ashby's Notetaker captures everything seamlessly inside the platform, freeing me to focus fully on candidates without juggling tools. I trust the notes are secure, accurate, and ready when I need them which helps our team give better feedback and make faster, fairer hiring decisions." - Dasha Nikolov, Technical Recruiting at Supabase

### AI-Assistance for post-interview workflows

Because these transcripts live in Ashby, they become one of the native data points we can leverage across multiple workflows. 

This means we can use the AI Candidate Assistant to answer questions like "Based on the job description what are the gaps this candidate has?" or specific queries about the interview like "Show me all the examples where they led through ambiguity."

![](https://a-us.storyblok.com/f/1017310/1036x633/7a86255b93/ai-notetaker-candidate-assistant.png)


We've taken great care to design AI-assistance to help you responsibly increase both feedback submission rates and time-to-feedback. This has a major impact on downstream recruiting metrics like time-to-hire and candidate NPS. 

By leveraging the "Auto-fill with AI" functionality you're able to draft feedback directly within the feedback form. 

![](https://a-us.storyblok.com/f/1017310/1036x726/70f9f2887d/group-514830681.png)

Importantly, these drafts are AI suggestions that come with references to source content for you to review so you’re always in control. 

If your team struggles with feedback completion rates, or timely feedback submissions this is a great way to enable your interviewers to write, review, edit, and submit feedback more quickly. 


> “I absolutely love the integration with Feedback Forms and specific interview questions. It makes summary and analysis a snap!" Peter Ludden People & Talent at SEI Development Foundation


### Streamlined AI Notetaking management

We know managing candidate consent and data retention policies in multiple places can become a huge administrative undertaking. It may even stop you from adopting a tool that would otherwise be extremely helpful. 

AI Notetaker leverages Ashby’s existing user management, data retention, AI policies, and candidate consent communication so you don't need to go through unnecessary hoops to approve and deploy note taking technology.

We also make it easy to manage access and usage. You can enable AI Notetaker for all interviewers or on an individual basis. 

![](https://a-us.storyblok.com/f/1017310/1308x446/d1356834f5/all-or-none.png)

This makes rollout and adoption straightforward because you're able to provide access straight away and you're not asking interviewers to train on a separate tool or workflow. 

You can also set up AI Notetaker to be enabled as a scheduling default across all interviews, at the individual template level, or per interview. 

![](https://a-us.storyblok.com/f/1017310/1050x467/a5fea52f2d/enable-it.png)

Candidate consent happens during scheduling with clear opt-out flows. Candidates have the opportunity to opt-out across multiple touch points and communications. 

![](https://a-us.storyblok.com/f/1017310/944x533/1ef8f61600/candidate-consent.png)

Additionally, your existing data retention policies apply to recordings just like any other candidate information.

### What happens when you start using AI Notetaker in Ashby?

> "We've found the Ashby AI Notetaker to be a valuable tool for streamlining our post-interview workflow. It allows our team to structure their feedback more efficiently, helping us maintain consistency across all our evaluations." - Ilaria Giacomelli, Talent Operations at Satispay


When interviewers can focus entirely on the conversation instead of documentation, the entire hiring process improves. 

Candidates experience more engaged, authentic interviews where their interviewer is fully present. The notes themselves become more objective and thorough since they capture everything said rather than what someone managed to write down. This completeness drives faster feedback submission and higher completion rates, cutting down the time needed for a typical feedback cycle.

The benefits extend beyond individual interviews. With transcripts living as a native data point alongside resumes, emails, and past feedback in Ashby, teams can evaluate candidates more comprehensively and unlock new workflows across all of Ashby. 

And because everything happens in one system rather than scattered across multiple tools, adoption is straightforward. Teams learn one workflow, manage one set of permissions, and keep all candidate data in a single, compliant location.


### Release and pricing details
AI Notetaker is releasing to public beta today. This means, during the public beta, teams can take advantage and use AI Notetaker right away as we roll out the final refinements.

![](https://a-us.storyblok.com/f/1017310/1262x856/952ed26167/ai-notetaker-wrap.png)


AI Notetaker is available to purchase across all plans and each plan includes 500 interviews to try AI Notetaker at no cost. 

Once you’re ready to move forward:
- Foundations customers can purchase the AI Notetaker bundle directly in app
- Plus and Enterprise customers can connect with their CSM for pricing details specific to their account

### AI Notetaker Bundle: Additional AI Credits Included 

When you purchase the AI Notetaker Bundle, you’ll also receive additional AI credits. These AI Credits are for usage-based features like [Fraudulent Candidate Detection and Management](https://www.ashbyhq.com/product-updates/introducing-fraudulent-candidate-detection-and-management-to-help-you-focus-on-legitimate-candidates) and [AI-assisted application review](https://www.ashbyhq.com/product-updates/ai-assisted-application-review). While the majority of [Ashby's AI features](https://www.ashbyhq.com/ai) are available without limits, certain data intensive features consume AI credits. 

The AI Notetaker bundle delivers the core note taking functionality above while also providing a generous allotment of AI credits so you don't need to worry about running out for usage-based AI features.  [See details on AI Credits here](https://docs.ashbyhq.com/ai-credits).

### Getting started with AI Notetaker

To get started, go to Admin > AI Notetaker and decide how you want to enable it for your org. Visit our [help center](https://docs.ashbyhq.com/ai-notetaker) for more details or [book a demo](https://www.ashbyhq.com/request-demo) to see learn how AI Notetaker in Ashby can help your team drive faster, more confident hiring decisions.


 AI Notetaker is built directly into Ashby to automatically record, transcribe, and summarize your interviews while providing AI-powered assistance to help drive faster, more confident hiring decisions.



Introducing AI Notetaker in Ashby for faster, more confident hiring decisions 

AI Notetaker

Today, we’re releasing Fraudulent Candidate Detection and Management to all customers in Ashby. It's designed to help you detect and mark candidates as fraudulent during your application review so you can focus on real candidates. 

See a full walkthrough below:

https://www.loom.com/share/f0ee83d8f7414239b42e90cfc1aadefe

Fraudulent candidates have become a huge disruption to hiring pipelines. They’re a drain on productivity for hiring teams and in extreme cases can expose sensitive company information.

We'll take a look at how you can use Fraudulent Candidate Detection and Management directly in Ashby and [how our approach](https://www.ashbyhq.com/blog/all/ashby-launches-the-first-ats-integrated-fraud-detection-system) prioritizes candidate experience while giving you full control of your fraud determinations. 

## Hires from inbound have been on the rise

Our [talent trends data](https://www.ashbyhq.com/talent-trends-report/reports/2023-trends-report-offer-acceptance-rates) has shown that inbound applications continue to make up a large percentage of hires.

![](https://a-us.storyblok.com/f/1017310/2400x1537/6c4573e0fa/accepted-offers-by-source-business-roles.png)

But, over time this channel has become saturated with fraudulent candidates resulting in inefficient review time, wasted interview hours, and a degraded experience for legitimate candidates. 

The data shows prioritizing inbound as a source for hire pays off but how can you effectively utilize this channel when volume + fraud are making it increasingly difficult?


## How Fraudulent Candidate Management in Ashby helps

In your Job settings you now have the option to define whether or not you want to set up automatic fraud detection for candidates that submit an online application.

![](https://a-us.storyblok.com/f/1017310/2830x1472/c0fd577b52/set-up-fraud.png)

This control gives you the ability to prioritize certain jobs where you believe more fraudulent behavior may exist. You also have the option to set this up as a default for all jobs. 

Applicants are then automatically run through multiple fraud checks as they apply to your jobs.

![](https://a-us.storyblok.com/f/1017310/2490x1244/c7e64c8fd0/automatic-detection.png)

We'll use signals related to:

- Device
- IP
- Email
- Phone

This method is designed to be unobtrusive to the candidate experience so as to not require any additional action on their end. We've also chosen a certain blend of signals and depth that are inherently hard for bad actors to spoof.

Applicants will now fall into two buckets that allow you to filter on and prioritize your application review:

1. Candidates with no fraud signals detected
2. Candidate with multiple fraud signals detected

This gives you the ability to, for example, do a first pass at applicants that meet your criteria (in combination with [AI-Assisted Application Review](https://www.ashbyhq.com/product-updates/ai-assisted-application-review)) and display no signals of fraud. 

![](https://a-us.storyblok.com/f/1017310/1404x988/b4a1475ecf/filter-fraud.png)

You now have an actionable method for approaching high-volume and potentially high-fraud pipelines.

Once you're in your application review you have all the details needed to make a determination on whether or not a candidate should be marked as fraudulent.

![](https://a-us.storyblok.com/f/1017310/2538x1378/bb9e3ef67c/app-review-fraud.png)

In this view you'll now see:
1. An AI summary of the fraud signals detected
2. The ability to drill down into the signals detected by clicking "show more"
3. A button to mark the applicant as fraudulent or not

Here we've prioritized surfacing all the information you need to make an informed decision. The AI summary makes it accessible to non-technical users and we'll also provide in-depth details in case you or your security team need to drill in one layer deeper. 


Because fraud signals live next to the application submission, resume data, and AI criteria you're able to move quickly in your determination.

![](https://a-us.storyblok.com/f/1017310/2880x1482/d2808445fb/other-context.png)

When fraud signals are detected we'll mark it as such on the candidate profile as well. Here you'll see all the details for each signal we're checking and we'll also expose convenient shortcuts like a "Check LinkedIn" if you want to go one step further to see what verifications they've done elsewhere.

![](https://a-us.storyblok.com/f/1017310/2666x1448/dfe8e0096f/candidate-profile-check-linkedin.png)

Because this is built into Ashby it's easily reportable. You can surface fraudulent trends on dimensions like job type or even keep a list of fraudulent candidates you've had over time. 

![](https://a-us.storyblok.com/f/1017310/1970x1430/bef10c2cdf/setting-up-fraud.png)

Fraudulent Candidate Detection and Management is included across all plans and uses your existing AI credits to perform checks on applicants. 

In the coming weeks we'll also be announcing some updates to our AI credit system so you can take full advantage of Fraudulent Candidate Detection and Management and [AI-Assisted Application Review](https://www.ashbyhq.com/product-updates/ai-assisted-application-review) without worrying about hitting a ceiling. More details to come soon!

For [full pricing details head here](https://docs.ashbyhq.com/candidate-fraud-detection). 

To get started, you can enable fraudulent candidate detection for specific jobs or as a default for your entire organization. If you’re interested in trying out Fraudulent Candidate Detection and Management in Ashby, you can also [book a demo here](https://www.ashbyhq.com/request-demo). 



Fraudulent Candidate Detection and Management in Ashby helps you detect and mark candidates as fraudulent during your application review so you can focus on legitimate candidates. 

Introducing Fraudulent Candidate Detection and Management to help you focus on legitimate candidates

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