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Modular, production-grade multi-agent framework powering 3 data science portfolio projects (healthcare, sports analytics, fintech) — built on LangGraph with zero additional cost.
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A modular, production-grade multi-agent framework built to power three data science portfolio projects spanning healthcare, sports analytics, and fintech. Built on LangGraph with a zero-additional-cost design philosophy — every component runs on free-tier or existing-subscription infrastructure.
Most data science portfolios show isolated, one-off projects. This repo takes a different approach: build the reusable architecture once — orchestration, memory, security, evaluation, tool governance — then apply it across three distinct industries and ML paradigms. The framework is the artifact as much as any single project built on top of it.
This is also a deliberate exercise in spec-driven, governance-first engineering practice: every component is specified and reviewed before it's implemented, every architectural decision is documented and traceable, and nothing ships without a defined evaluation and security posture.
The ecosystem is designed around a Runtime Stack — an authority and ownership hierarchy that keeps every layer's responsibilities cleanly separated. It governs which layer owns and enforces each concern; runtime events and requests may flow bidirectionally through named interfaces:
Agent Contract
↓
Execution Harness
↓
State Management
↓
Memory System
↓
Tool Layer
↓
Evaluation & Observability
↓
Security & Governance
Each layer is documented in a dedicated reference card (see docs/reference/), distilled from a structured review of current industry frameworks on agentic system design (MCP, A2A, SKILL.md, spec-driven development, agent evaluation, and security architecture). Every card has been through multiple rounds of senior-architecture-style critical review before being marked approved — see the build log in 00-MASTER-EXECUTION-PLAN.md.
Stays constant across every project (core/, skills/ infrastructure, mcp-servers/):
Selected from shared topics, language and repository description—not editorial ratings.
HiteshNathbuva /
Production-grade Multi-Agent AI Research Platform built with FastAPI, OpenRouter, and modular AI agents.
71/100 healthSwapped per project (projects/*/domain-skills/, data connectors, model selection):
| Project | Industry | ML Approach | Repo |
|---|---|---|---|
| Healthcare Fraud Detection | Healthcare / Compliance | Unsupervised anomaly detection | [link once published] |
| Fantasy Football Intelligence | Sports Analytics | Time-series forecasting + recommendation | [link once published] |
| Financial Analysis Platform | Fintech | Forecasting + portfolio optimization | [link once published] |
Each project repo depends on this one for its core agent infrastructure and consumes the shared Skills/Tools layer, customizing only the domain-specific layer described above.
ai-agent-ecosystem/
├── AGENTS.md # Master ecosystem specification — signed instruction artifact, v3.0 (Closure Plan Stage 7, Stage 10 patches)
├── docs/
│ ├── reference/ # Distilled architecture reference cards (the knowledge base) — all 7 APPROVED
│ ├── architecture/ # All 3 architecture artifacts complete (Stage 7): agent-contract-template.md, model-routing-table.md, tech-stack.md
│ ├── specs/ # BDD-style specs for core components, written before code (Phase 1+)
│ └── governance/ # Review/QA artifacts — emerged organically during Phase 0, not originally planned
│ ├── ecosystem-cohesion-review-rubric.md # Frozen v1.0 — reusable beyond this project
│ ├── PHASE-0-CLOSURE-PLAN.md # Complete — all 10 stages done, Phase 0 frozen at v0.1.0-phase0-freeze
│ ├── architecture-traceability-matrix.md # Concept → owner → references (Closure Plan Stage 2) — living document, updated every stage
│ ├── architecture-verification-specification.md # Post-implementation test plan — 38 scenarios (Closure Plan Stage 9, complete, 1.0 Approved)
│ ├── adr/ # Architecture Decision Records — ADR-001 through ADR-007 (Closure Plan Stage 8, complete)
│ └── cohesion-reviews/v1/ # Versioned historical review snapshot
│ ├── claude/ # 4-part independent review
│ ├── chatgpt/ # 4-part independent review
│ ├── architecture-review-board-synthesis.md
│ ├── review-reconciliation.md
│ ├── stage-10-internal-rescore.md
│ ├── stage-10-external-rescore.md
│ └── stage-10-reconciliation.md
├── core/ # The reusable "factory" — orchestrator, harness, memory, evaluation, observability, security
├── skills/ # Reusable SKILL.md library shared across all projects
├── mcp-servers/ # MCP tool connectors (file system, database, APIs)
├── projects/ # The three portfolio project implementations
├── tests/ # Test suites
└── 00-MASTER-EXECUTION-PLAN.md # Full build roadmap, status tracking, and progress log
docs/architecture/model-routing-table.mddocs/architecture/tech-stack.md for full rationaleFull rationale documented in docs/architecture/tech-stack.md.
Phase 0 is frozen at tag v0.1.0-phase0-freeze (commit 106a70f). All 10 Closure Plan stages are done — the architecture has been reviewed, corrected, and verified by dual independent reviews (internal + cold-read external), producing a reconciled FREEZE-READY-WITH-MINOR-PATCHES verdict. All 5 pre-freeze patches have been applied and verified, followed by a Working Principle #8 pre-tag consistency sweep (7 commits) that corrected discrepancies the patches themselves had missed. Phase 1 (Core Infrastructure) begins next — building core/harness/, core/memory/, core/security/, core/evaluation/, and core/observability/ against the 6 mandatory pre-build specs (S1-S6) before the first portfolio project implementation begins.
See 00-MASTER-EXECUTION-PLAN.md for the complete phase-by-phase roadmap, current status of every component, and a running progress log of design decisions.
Mohit Pammu — Data Analyst / Data Scientist in transition, building toward agentic systems and ML engineering roles. mohitpammu.github.io · LinkedIn
MIT — see LICENSE.