Building Signal For Hiring
We transform unstructured career data into structured, contextual intelligence for seekers & teams. Faster decisions. Better matches. Less noise.
The Challenge Of Modern Hiring
Application volume & noisy signals create drag for recruiters while seekers face opaque filters. We surface structure & context—fast.
Avg 48.7 applications per posting, overwhelming manual review.
Formatting + keyword bias silently filter strong candidates.
Sizing The Opportunity
Acceleration of AI adoption in HR + parsing automation forms a compounding wedge for talent intelligence. Dual-sided leverage expands TAM.
AI in HR (2024 → 2029)
High CAGR outpaces broader HR SaaS as intelligent orchestration replaces static workflows.
Resume Parsing Market
Automation of early-funnel qualification more than doubles extractive/value layers by 2029.
Intelligent Parsing & Scoring Pipeline
Raw documents evolve into structured, ranked, and contextualized talent intelligence via an 8-stage ML + NLP workflow.
Principles We Build Around
Context > Keywords
We care about trajectory, scope, domain & impact—not buzzwords.
Actionable Output
Feedback becomes resumes, outreach, interview prep & prioritization.
Dual-Sided
Seamless workflows for both seekers and hiring teams create compounding value.
Signal Preservation
Reduce loss across parsing, matching & evaluation pipelines.
Architecture & Tooling
Composable layers optimize ingest, transformation, and feedback surfaces while preserving extensibility.
Frontend
- Next.js: Hybrid rendering & route ergonomics.
- Tailwind CSS: Utility-first rapid design system.
- Framer Motion: Declarative animation primitives.
Backend & Data
- FastAPI: Async Python API throughput.
- PostgreSQL: Relational durability + indexing.
AI / NLP
- NLP: Entity + semantic extraction.
- ML: Predictive ranking & scoring.
- GenAI: Assistive generation surfaces.
- LangChain: Composable inference orchestration.
Dual-Sided Compounding Flywheel
Value to seekers increases structured supply; value to teams increases qualified demand—tightening the signal loop.
Seekers
- Detailed Resume Analysis
Actionable ATS-aligned recommendations.
- AI Job Field Prediction
Mapped trajectory + domain fit.
- Unlimited Free Access
Remove friction early in journey.
Employers
- Curated Candidate Dashboard
Structured profiles & rankings.
- Bulk ZIP Processing
Parallel ingest + extraction.
- Reduced Time-To-Hire
Prioritized signal + automation.
Differentiated Surface Area
Integrated seeker + employer workflow reduces system handoffs and amplifies structured feedback loops.
| Feature | Our Platform | B2B Parsers | B2C Builders |
|---|---|---|---|
| Detailed Seeker Analysis | ✓ | ✗ | ✓ |
| Employer Hiring Dashboard | ✓ | ✓ | ✗ |
| Bulk ZIP Uploads | ✓ | △ | ✗ |
| Unlimited Free Seeker Access | ✓ | ✗ | △ |
✓ Full | △ Limited | ✗ None
Target Adoption Vectors
High-volume recruiting + structured compliance needs accelerate ROI realization across initial sectors.
Sector Share & Focus
Data Model & Persistence
Normalized relational schema supports scalable parsing throughput, multi-tenant access control, and historical analytics.
Logical Architecture
Supports resume entity extraction, scoring artifacts, user account roles, and pipeline stage logging for observability.
Entity Relationships
Relational mapping across users, resumes, analyses, predictions, and hiring flows preserves referential integrity.
From Raw Text To Decisions
Capture
- Upload or bulk ZIP
- Multi-format parsing
- Auto validation
Structure
- Entity extraction
- Timeline building
- Skill normalization
Intelligence
- Gap & strength detection
- Role alignment scoring
- Career trajectory modeling
Generate
- Resume variants
- Cold outreach drafts
- Interview prep Q&A
Decide
- Signal ranking
- Prioritized actions
- Share / export
We're Just Getting Started
TalentSync is evolving fast. We're expanding deeper into structured career intelligence, recruiter collaboration, and predictive hiring signals.
© 2025 TalentSync AI