Introducing Recall v1.0
Hiring software should remember what happened.
Recall is the intelligence layer inside Hireytics that connects information collected throughout the hiring process — so teams can ask questions in plain language instead of reconstructing context manually.
Maya Evans
94% FitFinancial Analyst at Amber & Co
Amber & Co (2019 - now) • University of Manchester (Alliance Business)
“I'm familiar with financial planning tools like Adaptive Insights, which I used for multi-currency budgeting and quarterly board reporting.”
The information exists
Records are not the same as understanding.
Today, most hiring software is good at keeping records. A job has candidates. Candidates have resumes. Interviews have transcripts. Interviewers leave feedback. Assessments produce scores. Recruiters move candidates through stages.
The problem is that the person making the hiring decision still has to put it all together. Recall is built to change that.
Instead of searching through individual records and reconstructing context manually, you can ask.
What is Recall?
An assistant built directly into Hireytics.
Recall can reason across the hiring information available within your organization. The goal is simple: your hiring system should not just remember where information is — it should understand the context around it.
Your hiring system should not just remember where information is. It should understand the context around it.
The problem
The information is there. The thinking is still manual.
A hiring manager might have everything they need to make a decision — but that information is usually spread across multiple places.
Job Description
What are we actually looking for?
Resume
Does this candidate have the required experience?
Assessment
How did they perform?
Interview
What did they actually say?
Transcript
What evidence came up during the conversation?
Feedback
What did the interviewer think?
Pipeline
Where does this candidate currently stand?
That is the gap Recall is designed to address.
Ask the hiring system directly
Questions the way you would ask a colleague.
With Recall, a hiring manager can ask questions in the same way they would ask another person who understands the hiring process.
“Who should I move forward for this role, and why?”
Recall considers the requirements of the role alongside available candidate information and explains its reasoning using that context.
“What are the biggest weaknesses of this candidate?”
Instead of a generic resume summary, Recall considers information collected across the entire hiring process.
“What happened during this candidate's interview?”
Recall uses available interview information and transcripts to surface relevant context.
“Have we interviewed someone like this before?”
Recall looks beyond a single candidate and uses hiring history available within the system.
“Why did we reject this candidate?”
When the relevant information exists in the hiring record, Recall helps reconstruct the reasoning behind the decision.
HireyticsCompare between Saad & David for this Role should i move forward with and why ?
David Milleris the stronger choice for the Full Stack Developer position due to his higher JD match score of 88%, which indicates a better alignment with the job requirements. Both candidates received the same interview evaluation score of 7.2/10, but David's deeper backend capabilities in PostgreSQL & distributed microservices provide higher confidence.
| EVALUATION DIMENSION | DAVID MILLER | SAAD |
|---|---|---|
| JD Match Score | 88% (High Alignment) | 63% (Partial Alignment) |
| Core Strengths | Python, Django, React, PostgreSQL, Docker | JavaScript, React, Node.js, CSS, Agile |
| Voice Interview | 7.2/10 (High Technical Depth) | 7.2/10 (Strong Presentation) |
| Recommendation | ✓ Advance to Technical Round | Retain in Talent Pool for UI roles |
Not just a chatbot
Built around hiring data — not a window beside your ATS.
You could put a chatbot next to an ATS and call it an AI assistant. That doesn't solve the underlying problem. Recall understands the relationship between every stage of the hiring process — that relationship is what gives answers context.
The objective is to make the hiring system itself easier to reason about.
Connected context
One candidate is not the whole story
Hiring decisions rarely exist in isolation.
Recall uses accumulated hiring context rather than treating every candidate as a completely separate record. This information becomes useful when the system can connect it.
A candidate interviewed weeks ago
Another candidate who went through the same role
Feedback left in a different part of the workflow
A previous candidate with a similar background
Understanding why someone was rejected
Traditional software asks
“Where is this candidate?”
Recall aims to ask
“What do we know about this candidate?”
Then it helps answer
“What does that mean for this hiring decision?”
How Recall works
Structured data, semantic search, and contextual reasoning.
Structured hiring data
Some questions have clear answers in the database — candidate counts, pipeline stages, interview completion dates. Recall works with structured application data rather than asking a model to guess.
How many candidates are in a stage? Which candidates applied to a job?
Semantic understanding
Other questions require understanding meaning rather than matching exact words. Recall uses semantic retrieval to find relevant information across your hiring records.
Find candidates with experience similar to this person.
Contextual reasoning
Once relevant information is retrieved, Recall uses an AI model to reason over that context. The model receives information from your Hireytics environment — not generic knowledge.
Who should I move forward? — grounded in your actual hiring data.
Recall Intelligence Architecture
Live Context Reasoning Engine
Structured & Unstructured Data
- Resume parsed tokens (PDF/DOCX)
- AI voice interview transcripts
- Interviewer scorecard ratings
Semantic Context Graph
Links skills, salary expectations, role requirements, and interview quotes into a unified hiring vector index.
Cited Rationale Output
Generates natural responses with clickable proof citations directly linked to the candidate's interview transcript.
Evidence matters
An answer should explain why — not just who.
Hiring decisions are consequential. A useful system helps explain what requirements a candidate meets, what evidence supports that, what concerns exist, and where that information came from.
An AI answer is more useful when you can understand the context behind it.
Human judgment stays in the loop
Recall is an assistant — not the hiring manager.
It does not replace human judgment, and its recommendations should not be treated as automatic employment decisions. A hiring manager can review underlying information, challenge the recommendation, and make the final call.
Help people reason faster with better context — not remove them from the decision.
Recall v1.0
Understanding and reasoning across the hiring process.
Version 1.0 is intentionally focused on one core capability: helping teams understand what their hiring system already knows.
Understand candidates
Ask about qualifications, assessments, interviews, transcripts, feedback, and other available information.
Compare candidates
Use information across candidates to understand relative strengths, weaknesses, and fit.
Understand hiring history
Search and reason over relevant information from previous hiring activity.
Summarize context
Turn large amounts of hiring information into a concise explanation.
Natural-language questions
Interact with the hiring system without knowing exactly where information is stored.
What Recall v1.0 does not do
Clear boundaries, not magic promises.
Recall v1.0 is not designed to autonomously run your entire recruiting operation. Answer quality depends on the completeness of information in your hiring system — and we would rather be clear about that than present a chatbot as magic.
- Does not replace Recruiters
- Does not replace Hiring managers
- Does not replace Interviewers
- Does not replace Employment decisions
- Does not replace HR policies
- Does not replace Legal review
Built around the hiring lifecycle
Each step adds context. Recall connects it.
Recall becomes more useful as the hiring record becomes richer. Instead of treating every step as separate information, it connects context across the full lifecycle.
Context Flows Forward Through Every Stage
1. Requisition Setup
UI/UX Designer • Full-time
Recall Memory:Recall analyzed JD requirements & generated customized screening rubric.
2. Resume Ingestion
128 applicants parsed
Recall Memory:Recall auto-matched top 15 profiles with >85% semantic relevancy.
3. AI Voice Interview
45-min technical session
Recall Memory:Recall extracted 6 verified skill quotes regarding Figma & user testing.
4. Offer & Onboarding
Package: $84,000 agreed
Recall Memory:Recall transferred interview strengths directly into 90-day onboarding goals.
The beginning of an agentic hiring system
From understanding to recommendation to action.
Recall v1.0 is primarily about understanding. Actions should come after the system can reliably understand the context behind them — with humans remaining in control.
Now — v1.0
Understand
Connect and reason across hiring context
Future
Recommend
Surface informed suggestions with evidence
Future
Act
Prepare actions while keeping humans in control
Future examples: “Move the strongest candidate to the next stage.” “Schedule interviews with the three candidates I selected.” The system would propose or prepare the action — the user remains in control.
Institutional Talent Memory
Cross-Lifecycle Intelligence
Interviewed 6 mos ago for Mid-Level role
Hired UI/UX Designer
Why we built Recall
Storing information and understanding it are different problems.
We kept seeing the same pattern: systems getting better at storing information, while recruiters still had to remember where something was stored and hiring managers opened six records to answer one question.
Recall is our answer to that problem.
Built into Hireytics
Recall is not a separate product beside Hireytics. The same system that manages your hiring workflow provides the context Recall uses.
- Jobs
- Candidates
- Assessments
- Interviews
- Feedback
- Hiring stages
- Candidate records
What comes next
Remember more. Understand more. Do more.
Better memory
Connect more hiring history and make that information easier to retrieve.
Better reasoning
Improve quality, transparency, and reliability across complex hiring questions.
Controlled actions
Allow Recall to take useful actions inside the hiring workflow while keeping humans in control.
Recall v1.0
Your hiring system already has the information.
Recall helps you use it.