Vecorra for employers

Hire AI talent with evidence, not promises.

Every candidate on Vecorra arrives with a scored, AI-verified evidence profile — three-part assessment breakdown, Vecorra Evidence Report, verified tool stack, and a fit score against your exact role.

  • Zero CV fabrication risk
  • Vecorra Evidence Reports
  • UK GDPR compliant
  • Explainable scorecards
Hiring team reviewing verified candidate profiles together
Why Vecorra beats recruitment as usual

Every frustration solved.

CVs that claim everything but prove nothing

Every candidate arrives with a three-part scored evidence profile, generated by our AI assessment engine.

Hours lost screening unqualified applicants

Open the role's leaderboard with applicants already ranked on job-specific assessment evidence — no screening calls needed.

Generic job boards that don't understand AI roles

Four role-specific tracks — Data Scientist, ML Engineer, MLOps, GenAI/LLM — each with distinct competencies and tool stacks.

No way to compare candidates apples-to-apples

Every candidate is assessed on the same three dimensions: theory, practical coding, and case study. Scores are standardised across the cohort.

Platform features

Six capabilities. One hiring workflow.

From your first browse of the evidence board to confirming a placement — all in one place.

Evidence Profiles

Every candidate in the pool has a Vecorra Evidence Report — score breakdown by dimension, verified tool stack, strengths, and areas to probe. Not a CV. Evidence.

Per-role Leaderboards

Every role you post gets a job-specific assessment generated from the description. Applicants are ranked on knowledge, coding and case-study evidence, so you can invite the top candidates to interview in one click.

Vecorra Evidence Reports

After a candidate completes their pipeline, Vecorra synthesises all assessment data into a structured recommendation — covering strengths, concerns, stack alignment, and hiring confidence level.

Role-Track Assessments

Assessments are customised by role: Data Science candidates face statistical inference and experimentation questions while GenAI engineers are tested on RAG design and LLM evaluation.

Tool-Stack Matching

Specify the exact tools your team uses — PyTorch, FastAPI, Terraform, LangChain — and Vecorra applies a stack-alignment bonus that surfaces candidates who have already used them in assessments.

Interview Hub

Schedule, manage, and track interviews end-to-end. Structured feedback forms, outcome recording, and candidate communications all in one place.

Interview stage automation

We handle your first two screening stages.

Vecorra replaces CV screening, first-round technical filtering, and take-home challenge administration — so your team only meets candidates who have already proven they can do the job.

1

CV screening eliminated

Every candidate completes a structured Knowledge Test before they reach your inbox. No more sifting self-reported CVs.

2

Technical filtering automated

Role-specific Coding Challenge and Case Study replace take-home tests. Scores are standardised and tamper-evident.

3

You take the final interview

Receive a pre-scored shortlist with evidence profiles, strengths, concerns, and a custom interview guide ready to use.

What you receive per shortlisted candidate

Full three-part assessment scorecard
Vecorra Evidence Report with stack alignment
Strengths and risks summary
Custom interview guide for the final human stage
Audit trail showing why the candidate was recommended
Percentile ranking against the full cohort
Role-specific assessments

No more generic AI tests.

Each track has its own Knowledge Test, Coding Challenge, and Case Study — calibrated to the competencies and tools actually used in that role.

Data Scientist

Statistical rigour, experimentation, and interpretable model delivery.

Statistical inference
Feature engineering
Model interpretability
Experiment design
scikit-learnpandasstatsmodelsSQL

Case study topic

A/B test design and interpretation on a live product dataset

ML Engineer

Production model deployment, serving infrastructure, and monitoring.

Model serving & APIs
Latency optimisation
Pipeline architecture
Monitoring
PyTorchFastAPITorchServeDockerKubernetes

Case study topic

Optimising a model-serving stack to reduce p99 latency below 200ms

MLOps Engineer

CI/CD for ML, model registry, drift detection, and infrastructure automation.

CI/CD for ML
Model registry & versioning
Drift detection
IaC
MLflowKubeflowAirflowTerraformGrafana

Case study topic

Designing a model registry and automated retraining pipeline from scratch

GenAI / LLM Engineer

Prompt engineering, RAG architecture, evaluation frameworks, and production LLM systems.

Prompt engineering
RAG design
LLM evaluation
Guardrails & safety
LangChainLlamaIndexOpenAI APIPineconeRAGAS

Case study topic

Building an enterprise RAG pipeline with hybrid retrieval and source attribution

Trust and integrity

Built so you can defend every hire.

AI-scored pipelines are only valuable if you can trust and explain the results. Vecorra includes nine layers of assessment integrity built in.

AI proctoring & tamper-evident sessions

Every assessment session is AI-monitored. Unusual behaviour — tab switching, copy-paste patterns, or anomalous timing — is flagged automatically.

Plagiarism & code-similarity detection

Submissions are cross-checked for plagiarism and code similarity against the candidate pool and public repositories. Matched submissions are escalated for human review.

Question randomisation per candidate

No two candidates receive the same question set. Questions are drawn from a calibrated bank and randomised per assessment to prevent sharing.

Retake policy & anomaly detection

Retake attempts are strictly limited. Any outlier result — a score significantly different from a candidate's prior performance — triggers a review flag before the profile is published.

Human-review override

Any employer or programme manager can request a human review of a candidate's assessment. Vecorra reviewers audit the evidence and issue a verified override note.

Fairness & consistency scoring

All assessments are normalised against the cohort. Score distributions are monitored for demographic consistency, and any statistically significant bias is surfaced for audit.

Explainable Vecorra scorecards

Every score comes with a human-readable rationale — not a black-box number. You see exactly what the candidate did and why they scored as they did.

Full audit trail per candidate

Every assessment action — start time, question sequence, submission content, AI score, human flag — is logged and available to download. Defensible hiring decisions, on record.

Powered by Trillectra AI · UK GDPR compliant

Assessment methodology validated through the TechLocal programme. All data processed under UK GDPR with EU-region storage. ISO 27001-aligned controls.

Employer pricing

Simple, outcome-based pricing.

No per-CV fees. No placement commissions. Flat monthly access to the full verified talent pool.

Starter

Job-specific assessments and a ranked leaderboard for every role.

£299/mo
Unlimited Evidence Profile access
Per-role candidate leaderboards
Tool-stack matching
Interview scheduling
Post up to 5 job listings
Start hiring
Most popular

Growth

Unlimited roles, AI-assisted screening interviews, and advanced analytics.

£599/mo
Everything in Starter
AI screening interviews
Weekly matched-talent digest
Unlimited job listings
Advanced match analytics
Priority placement pipeline
Accelerate hiring

Enterprise

Dedicated account manager, bulk exports, and API access.

£1,499/mo
Everything in Growth
Custom assessment blueprints
Dedicated account manager
Bulk CV downloads
API access
Custom reporting
Talk to sales

All plans include a 14-day free trial. No credit card required.Compare all plans →

Ready to skip the screening calls?

Use Evidence Profiles to hire AI talent faster, with proof attached to every candidate.