Pain: Stale jobs and application black holes
Roles require reconfirmation every 30 days and pause automatically when an application waits over 7 days for employer review.
The faster path to credible AI hiring
Upload your resume. Let your work speak.
Talent Hub turns your resume into an editable, evidence-rich AI profile in one upload - then lets you prove real agentic skill on a recorded, auto-graded task instead of arguing about keywords.
New here? See exactly how it works, step by step Hiring AI talent? Build an accountable hiring workspace
AI-assisted profile You review every field Private by default
Your launch sequence
Resume → opportunity
Uploading sends the file to our AI parser to draft your profile. It is processed in memory and never stored.
1
Profile drafted
Skills, experience, links, and summary are structured.
2
You stay in control
Review and edit every suggestion before saving.
3
Apply with proof
Use visible projects or verification - not keyword tricks.
No auto-publish. No invented achievements.
Identity linked
One accountable profile
Evidence layered
Signal source stays visible
Agent graded
Recorded run, scored rubric
Permissioned
Candidates control access
Not another application graveyard
Four painful job-portal defaults are prohibited by the product.
This difference is enforced in workflows and data - not written as a marketing promise.
Pain: Resume keyword theatre
Matching keeps self-report, projects, and evaluation-verified skills at different evidence levels.
Pain: Recruiter spam and contact harvesting
Candidate email stays private until the candidate accepts a role-specific introduction.
Pain: Opaque ranking
Every match exposes criteria, confidence, evidence sources, and gaps instead of one unexplained score.
The part no job board has
Anyone can claim “agentic AI”. Here you run an agent and we grade the recording.
Point your own agent at a live task server. Every tool call it makes is recorded server-side as an ordered trajectory, then scored against a published rubric. You cannot rehearse the answer, and we cannot be charmed by a resume.
The run is recorded, not reported
Your agent authenticates with a one-time token and works a real multi-step task. Arguments, results, retries, and dead ends are all captured. The transcript is the evidence.
Six dimensions, published weights
Task success, tool correctness, error recovery, efficiency, loop avoidance, and verification discipline. Every score shows which criteria passed and which failed, so a result can be argued with.
One unsafe action is a fail
Criteria marked critical - irreversible or policy-violating actions - are a hard gate. An agent that issues a refund it was told not to fails outright, no matter how tidy the rest of the run was.
What an employer sees instead of a keyword
Self-reported skill
Counts least
Shipped project
Counts more
Graded agent run
Counts most
Match scores never blend these into one opaque number. The source of every signal stays visible on the profile and in the match breakdown.
Two journeys. One shared language.
Make capability easier to prove and easier to hire.
For AI engineers
Turn your work into a hiring signal.
Connect projects, explain engineering decisions, complete role-specific evaluations, and control what employers can discover.
- Evidence profile
- Readiness pathway
- Verified skill matrix
- Matched opportunities
For hiring teams
Assess depth before the first call.
Review evidence, technical judgment, deployment experience, and role fit without reducing candidates to keywords or one opaque score.
- Verified evidence
- Explainable matching
- Applicant pipeline
- Candidate-controlled discovery
The complete journey
Learn. Build. Prove. Connect.
Course completion is useful context. It is never treated as proof of job readiness by itself.
Read the evaluation standard- 01
Learn
Develop practical foundations through Thrive With AI or equivalent experience.
- 02
Build
Document real systems, decisions, tradeoffs, outcomes, and limitations.
- 03
Prove
Complete a role-specific scenario with automated checks and human review.
- 04
Connect
Choose when verified evidence can be discovered by approved employers.
Evidence that keeps its context
A skill is only as credible as the evidence behind it.
Every signal is labeled so a recruiter can distinguish a candidate claim from learning, project proof, and structured evaluation.
Self-reportedLearning completedProject demonstratedEvaluation verified
Python & software engineering
LLM application development
RAG & retrieval quality
Agent design & orchestration
Evaluation & observability
System design & architecture
Reliability & failure handling
Security & responsible AI
Deployment & operations
Technical communication
Initial tracks
Built around real AI engineering work.
Track definitions and evaluation policies will be versioned as the platform expands.
01
AI / ML Engineer
Models, data, deployment
02
Generative AI Engineer
LLM systems and evaluation
03
RAG Engineer
Retrieval, grounding, citations
04
Agentic AI Engineer
Agents, tools, orchestration
05
AI Platform Engineer
Infrastructure, reliability, scale
“Day 1 Ready” cannot be bought, claimed, or earned by attendance.
Policy gated
Minimum overall and critical-dimension standards.
Evidence required
Required artifacts and evaluation results must exist.
Human decision
A structured reviewer decision is always attributable.
Integrity protected
Unresolved flags block verification.
Help set a better standard for AI hiring.