AI Market Intelligence Platform. A market-radar that scientists trust.
8-stage LangGraph pipeline with AES-256-GCM encryption and expert-knowledge encoding.
The AI Market Intelligence Platform is a production-grade system built by Enso Labs for a Fortune 500 manufacturer that surfaces auditable commercial signals from scientific literature, patents, and regulatory filings — replacing weeks of manual research with a single auditable pipeline.
The Challenge
The client's Battery Insulation Division needed to surface emerging commercial opportunities from scientific literature, patents, and regulatory filings — replacing manual research processes that took weeks.
What We Built
- Designed the "Expert Lens" — a 9-rule expert-knowledge encoding framework with toggleable relevance rules
- Built an 8-stage LangGraph pipeline with 4 parallel fetchers and ReAct agents
- Processed 731 documents, curated 111 sources, surfaced 16 market developments
- Delivered AES-256-GCM encrypted dashboard with signal cards and RWW scoring
- Go/no-go commercialization milestone validated by lead scientist
Outcomes
Quick Reference
- Project
- AI Market Intelligence Platform
- Client
- Fortune 500 Manufacturer × Board of Innovation
- Sector
- Advanced Materials / Manufacturing
- Engagement
- Strategy → Build → Ship
- Stack
- LangGraph · Python · Claude · MCP
- Delivered
- April 2026
- Studio
- Enso Labs — ensolabs.ai
Frequently Asked Questions
What is the AI Market Intelligence Platform?
The AI Market Intelligence Platform is a production-grade system built by Enso Labs for a Fortune 500 manufacturer. It uses an 8-stage LangGraph pipeline with 4 parallel fetchers and ReAct agents to surface auditable commercial signals from scientific literature, patents, and regulatory filings — processing 731 documents and surfacing 16 validated market developments.
How does the Expert Lens expert-knowledge encoding work?
The Expert Lens is a 9-rule expert-knowledge encoding framework where each rule represents a domain-specific relevance criterion defined by the client's scientists. Rules are toggleable, allowing scientists to tune signal sensitivity by market vertical. The system encodes expert judgment into the AI pipeline so that relevance ranking reflects scientific priorities rather than generic keyword matching.
Related Work
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