TEN: Talent Exchange Network

Most Web3 and AI startups drown in unqualified applicants the moment a job goes live — fifty resumes by Friday, no honest way to rank them by Monday. TalentNode is a job-board engine with AI candidate ranking built in, so the top ten matches surface on the recruiter's dashboard before anyone has finished their coffee. The same engine can be re-skinned for a second hiring vertical, then a third, without standing up a new codebase.

The problem it solves

A single Web3 or AI engineering role typically attracts 80-150 applications inside two weeks. Generic boards (LinkedIn, Web3.career, Indeed) hand the recruiter a flat list with no signal-to-noise filter. Hiring managers then burn 6-10 hours per role manually scanning resumes, and most still hire on gut feel rather than a defensible match score. A bad senior hire on a six-person team costs $80K-$180K in salary, ramp-up, and replacement — on a small team, getting hiring wrong is not a percentage problem, it is the company's runway.

The second problem is operator-side. Existing job-board products are single-use SaaS: one platform, one brand, one taxonomy. An accelerator that wants to run a hiring vertical for its portfolio, a DAO that wants a cohort job page, or a recruitment agency that wants to operate a private board for clients cannot get there without a $40K-$150K custom build or a permanent per-seat licensing line item. Every new vertical means a new codebase to maintain — or a yearly fee to whoever already owns one.

Who needs this most

• Early-stage Web3, AI, and FinTech startups (5-30 staff) hiring 2-6 roles per quarter — the founders who personally read every resume because they cannot yet afford a recruiter, and who need the top-10 match list ready before their next standup.
• Accelerators and incubator funds with 20-80 portfolio companies who keep being asked by portfolio founders for hiring help, and need to operate a branded jobs vertical without standing up a separate codebase per cohort.
• Recruitment-agency operators specializing in crypto, AI, or cybersecurity verticals who want their own dark-themed, SEO-first board under their own domain and brand, but do not want to write, run, or maintain the infrastructure.

The moment this hurts most: any Friday afternoon when a role has 80+ applications, the recruiter has 30 minutes between meetings, and the next standup expects a shortlist.

The solution — in plain terms

TalentNode runs as a single deployable engine that can be themed and re-branded for multiple hiring verticals — a job board for Web3, another for AI, another for cybersecurity — all from one codebase, one database, one operator dashboard. The God Architect (the operator) controls colors, fonts, layouts, approval workflows, credit pricing, and which integrations are live, all from a UI rather than a code change.

The day-to-day for the operator: a recruiter or founder registers, creates a company profile, and posts a job — paying with credits, either fiat via Stripe or crypto via a native BTC/ETH/USDT deposit wallet. Applications come in either through the platform's own application form or through an external redirect with click tracking; either way, they are stored, scored, and surfaced on a recruiter dashboard with a live AI ranking. Job seekers browse, bookmark, apply, track every application they have submitted, and filter out roles they have already applied to. The God Architect sees every metric across every vertical from a single dashboard.

The AI ranking is the centerpiece. Every application runs through a three-layer scoring pipeline: regex and keyword matching against the job's required skills (0-40 points), structured signal scoring on years of experience / location fit / salary fit (0-25 points), and an LLM semantic pass that emits a one-paragraph strengths-and-concerns summary (0-35 points). The output is a 0-100 composite, color-coded on the dashboard, with the top 10 highlighted as the recruiter's day-one shortlist.

Value delivered — what you get

• Cuts recruiter screening from 6-10 hours per role to a 10-minute review of the top 10 — the three-layer scoring pipeline ranks every applicant 0-100 and surfaces the ten strongest matches, with an LLM-written summary attached to each.
• Stands up an entire branded hiring vertical in a day, not three months — config.ini + setup.sh + docker compose up = a live board with PostgreSQL, Redis, Nginx with SSL, all theme controls, and a seeded operator account.
• Replaces a $15K-$50K-per-year stack of CryptoJobsList listings, ATS subscriptions, and SEO tooling — public listings, applicant tracking, programmatic city/tag SEO pages, and credit-based monetization all sit in one codebase.
• Catches the candidates a keyword filter would miss — the LLM semantic layer surfaces strong applicants whose resumes do not use the recruiter's exact vocabulary, so good hires are not lost to wording mismatches.
• Keeps the AI bill predictable via tiered models — Haiku screens every applicant; Sonnet only re-analyses the top 50 per job. At a 50-applicant posting the per-job AI cost lands near $0.20.
• Puts the operator in control of pricing, branding, and approval policy without a redeploy — every business setting (credit-pack prices, auto-approval toggles, accent color, list-versus-magazine layout) lives in the GlobalSettings table and changes from the dashboard.

Where it delivers outsized value

• Web3 and crypto accelerators and DAOs — programs that want a hiring vertical branded to their cohort, with crypto payment rails already wired in (BTC, ETH, USDT) so portfolio founders can buy credits without a Stripe friction point or a KYC delay.
• AI-services agencies and FinTech operators running multiple sub-brands — one codebase serving several themed verticals, with one central operator dashboard for cross-vertical reporting. The kind of build that would otherwise consume a quarter of engineering time per additional vertical.
• Recruitment-agency operators in regulated or jurisdictionally-segregated markets — Docker-deployable on the operator's own VPS or air-gapped infrastructure, no SaaS lock-in, no candidate data flowing to a third-party ATS, no per-seat surcharge as the agency grows.

Distinctive features — why this over the alternatives

• Three-layer AI candidate scoring with cost control built in — regex (0-40 pts) + structured signals (0-25 pts) + Claude LLM semantic pass (0-35 pts), batched every 15 minutes via BullMQ, Haiku for screening and Sonnet only for the top 50. Recruiters get a defensible shortlist; the operator's AI bill stays inside a budget cap set in the dashboard.
• Multi-vector architecture from one codebase — the GlobalSettings table is a singleton injected as CSS custom properties on every render. Accent colors, fonts, layout mode (CryptoJobsList-style list vs. magazine 3-card grid), pricing tiers, and approval policy all change without a deploy.
• Human-first job listings — every role shows the actual recruiter or founder who posted it ("Posted by Joshua at Superis Labs, Mar 26, 2026"), not a faceless company entity. Warm postings get more qualified applications than cold corporate listings.
• Credit-based monetization, fiat and crypto in one flow — Stripe checkout for fiat (1/3/10-credit packs at operator-set prices) and a native BTC/ETH/USDT deposit wallet for crypto, both feeding the same credit balance. Credits never expire; the operator changes pricing without touching code.
• SEO-first by default — server-rendered job pages, JSON-LD JobPosting schema on every detail page, programmatic city pages (/city/singapore), tag pages (/tag/solidity), auto-generated sitemap and RSS feed. Built to land in Google for Jobs from day one.
• Self-hostable end-to-end — Postgres + Redis + Next.js + Nginx + uploads volume all in one Docker stack. No managed-SaaS dependency in the critical path. One operator VPS runs the full stack including SSL termination and a worker container.

Under the hood — built to last

TalentNode runs on Next.js 16 with the App Router, TypeScript in strict mode, Tailwind 4, and PostgreSQL 16 — boring, well-supported foundations chosen to still be running in five years. Authentication uses JWT (jose + bcrypt) on an access/refresh-token pattern with a 5-tier role hierarchy. Application state lives in Zustand stores with localStorage persistence; theming flows from the GlobalSettings table to CSS custom properties on the html element, so re-skinning a vertical never touches a component. The AI scoring engine is split into three composable layers — two pure-TypeScript scorers and one Anthropic API call — so the operator can swap or tune any layer without unwinding the others. Everything ships in Docker; one VPS runs the full stack including Nginx with Certbot SSL, Postgres, Redis, the Next.js app, and a worker container.

Current maturity

TalentNode is in active development with all foundational phases complete: authentication and the 5-tier role hierarchy, the God Architect operator dashboard, the public job board (both list and magazine display modes), seeker and recruiter flows, the company directory with running-logo marquee, the three-layer AI scoring pipeline, credit-based payments (Stripe + crypto deposits), the events system (platform events + company-hosted events), the audit log, and a programmatic SEO surface for city and tag pages. Roughly 16,200 lines of TypeScript across 40 pages, 47 API routes, and a 20-model Prisma schema. Started 2026-03-30 per the project's own whitepaper; most recent source activity 2026-05-25. The platform runs in a dev Docker stack today and has a production stack already defined (docker-compose.prod.yml with Nginx + Certbot). It is not yet positioned as a public live product — pre-launch hardening (final deploy script, demo seeding, monitoring) is the remaining gap before the first paying tenant.

Roadmap — what's next

The next milestone is a public launch as a paid hiring engine for Web3 and AI startups. Phase 6 work covers a salaries page (aggregated, anonymized salary data as a new programmatic-SEO surface), a blog and content section for inbound SEO, a platform-activity feed, and a partner API tier for third-party aggregators. After that, the multi-vector architecture moves from latent capability to a marketed product: ecosystem tenants (accelerators, DAOs, agencies) get a themed sub-vertical on the operator's platform, paying a tenancy fee rather than commissioning a separate build.

Further out, the AI scoring pipeline becomes a standalone product surface — operators of other ATSs can submit applications to a scoring API and receive a composite score and breakdown back, billed per evaluation. That positions TalentNode not just as a job board but as the underlying hiring-intelligence rail for partner platforms.

Working with the architect

TalentNode is available in three engagement modes. A startup, accelerator, DAO, or recruitment agency can commission a custom build — a themed vertical deployed on the buyer's own infrastructure, with branding, taxonomy, and integrations tuned to their cohort or market. An existing hiring platform can extend its own pipeline with the three-layer AI scoring engine described here, integrated directly into the buyer's stack. And operators with their own technical teams can engage in ecosystem tenancy — running their hiring vertical as an authenticated sub-brand on the architect's platform without owning the infrastructure themselves. Reach out via sintegrium.io or LinkedIn for a 30-minute scoping call.

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Built by Yurii Staryk · Solution Ecosystem Architect