PAGE / 03 Work

AI Transformation shipped.
Production-grade.

Enso Labs has delivered AI transformation for Fortune 500 organizations — production intelligence platforms, AI Centers of Excellence, and autonomous trading systems. Four representative engagements.

↳ CS / 01   AI Market Intelligence Platform↳ CS / 02   Heller AI Center of Excellence↳ CS / 03   Enso Trading Terminal↳ CS / 04   Enterprise AI Enablement
CASE / 01
ClientFortune 500 Manufacturer × Board of Innovation
SectorAdvanced Materials
EngagementStrategy → Build → Ship
StackLangGraph · Python · Claude · MCP
DeliveredApril 2026

Gore M2 Intelligence Hub.
A market-radar that scientists trust.

Gore Lens · 9 rules
Temp floorON
Material classON
Chemistry scopeON
PFAS sensitivityREVIEW
Market sizeON
LiabilityON
RecencyON
NoveltyON
200°C gapON
Surfaced signals · 16
High-temp PTFE alternative · pilot data
RWW 0.91recency 4dpeer-reviewed
Aerospace insulation · novel chemistry
RWW 0.84recency 12dcommercial
Battery separator · 200°C threshold beat
RWW 0.78recency 9dpatent
Pipeline · live
fetch · arxivOK
fetch · usptoOK
fetch · tradepubsOK
fetch · web214
react · screen731
react · cluster111
react · score16
encrypt · AES-256-GCM●
publish · CEEX●
review · lead-sciQUEUE

The brief

Gore needed a defensible go/no-go signal on emerging high-temperature materials markets — fast, but auditable enough that lead scientists would actually trust the output.

What we built

Gore M2 Intelligence Hub — a production-grade, AES-256-GCM encrypted research dashboard powered by an 8-stage LangGraph pipeline with 4 parallel fetchers and ReAct agents.

  • Proprietary Gore Lens — expert-knowledge encoding framework with toggleable, MCP-compatible relevance rules
  • Signal-card architecture with RWW (Real / Win / Worth) scoring and full evidence trails
  • 9 configurable Gore Lens rules — temperature floor, material class, chemistry scope, PFAS sensitivity, market size, liability, recency, novelty, 200°C gap
  • CEEX integration with token mapping into Gore’s internal scoring tools

Outcome

731
Documents processed in pipeline run
111
Sources curated & clustered
16
Market developments surfaced

Novel signals validated by lead scientist. Measurably higher relevance with Gore Lens ON vs OFF. Go/no-go commercialization milestone delivered April 2026.

View case study
CASE / 02
ClientHeller Agency
SectorHealthcare / Pharma
EngagementAI Center of Excellence
StackMindStudio · RAG · N8N · GA4
ComplianceNIST RMF · FDA · MLR · PRC

An AI Center of Excellence
that ships pharma campaigns in 2 weeks.

Brand knowledge bases · 5
Tolmar / Eligard● ACTIVE
Tolmar / Rubraca● ACTIVE
Eton / DESMODA● ACTIVE
Eton / INCRLEX● ACTIVE
SpyGlass● ACTIVE
Active automations · 8
Daily optimizer · Google Ads06:00 ET
MLR pre-flight scanon-commit
Competitor mention ratehourly
HCP search-intent rollupdaily
Brand voice eval (RAG)on-draft
AI Search visibilityweekly
Campaign brief genon-demand
Looker → Slack digest07:00 ET
Concurrent campaigns6 RUNNING

The brief

Heller — a full-service pharma agency — needed an AI Center of Excellence that respected MLR/PRC review, FDA compliance, and brand voice across multiple client portfolios.

What we built

  • End-to-end AI Center of Excellence with NIST AI RMF and FDA / MLR / PRC compliance baked in
  • 2 AI-powered applications on MindStudio with RAG retrieval grounded in 5 brand knowledge bases
  • AI Search Strategy for pharma — competitive intelligence on AI mention rates across LLMs
  • Google Ads management across 6 concurrent pharma campaigns + 8 active automations

Outcome

75%
Pilot-to-production
83%
Faster campaign launches · 3mo → 2wk
35%
Time savings on weekly reporting
View case study
CASE / 03
ClientInternal · Enso Labs
SectorFinancial Services / FinTech
EngagementProduct build & operate
StackPython · LangGraph · Alpaca · Hyperliquid
Status● Live in production

Enso Trading Terminal.
We build what we sell.

●  LIVEEQUITIESOPTIONSCRYPTODEFIP/L 24h + 2.41%
News intelligence
NVDA · earnings beat+0.92
SOFI · downgrade-0.61
BTC · ETF inflow+0.74
SPY · CPI print+0.18
scanned 2,134 articles · 14m
Options flow
NVDA 1100C · 5/2UNUSUAL
TSLA 280P · 5/9SWEEP
SPY 545C · 5/16BLOCK
AAPL 220C · 5/30SWEEP
tracked 18,402 contracts
Crypto · DeFi
HL · ETH long+1.84%
HL · SOL long+0.42%
altFINS scan · 24h37 setups
signal-forge · v2●
funding-rate guard ON
signal-forge-v2 · build #1842 · all checks passedkill-switch ARMED · risk caps OK

The brief

Internal product. The hypothesis: a single operator can run a multi-agent trading desk if the architecture is right. The proof point: revenue while we sleep.

What we built

  • News Intelligence Trading Platform — news-driven trading algorithms across equities & crypto
  • Public.com Trading Dashboard — Python web app (app.py · sr_engine.py · research.py)
  • Public Trading Central Command — multi-agent trading command center
  • Automated Crypto Trading Program with altFINS integration · signal-forge architecture
  • Hyperliquid DeFi investment strategy engine
  • Options Lab with strategy testing guide · brokerage API integration (Alpaca, Public)
  • GitHub version control · nycsav/signal-forge-v2

Outcome

Production trading infrastructure spanning equities, options, and crypto / DeFi. Demonstrates full-stack builder capability — strategy to deployed system, principal-led end to end.

View case study
CASE / 04
ClientsCiti · JPMorgan · Amex · Google · Microsoft · T-Mobile
SectorCross-industry · Enterprise
EngagementCohort enablement
Cohort size8–15 leaders

Enterprise AI Enablement Programs.

The brief

Senior leaders need to make AI decisions, not slide-deck AI decisions. We run hands-on cohorts that end with a working artifact.

Outcome

3mo
Time-to-first-value
75%
Pilot-to-production
8–15
Person cohorts

Legacy engagements include Citi (Web3/fintech strategy), AT&T / BBDO (“It Can Wait” — 5MM+ pledges), American Express / Rokkan (50% social following increase), Google (Google+ launch strategy), and Jublia (omnichannel HCP/patient program).

View case study
§ 05 Common questions

What we build, and the proof.

What kind of AI systems does Enso Labs build?+ open

Enso Labs builds production-grade agentic AI systems — multi-agent orchestration with LangGraph, RAG knowledge systems, MCP server integrations, AI Centers of Excellence, and autonomous trading platforms. Every system ships with eval harnesses, observability, and compliance layers. Recent engagements include an AI Market Intelligence Hub for a Fortune 500 manufacturer, a pharma AI Center of Excellence, and the Enso Trading Terminal.

Does Enso Labs have production AI case studies?+ open

Yes. Enso Labs has four published case studies: (1) an AI Market Intelligence Platform for a Fortune 500 manufacturer with an 8-stage LangGraph pipeline, (2) an AI Center of Excellence for Heller Agency in pharma with 83% faster campaign launches, (3) the Enso Trading Terminal — a live autonomous trading system spanning equities, options, and crypto, and (4) Enterprise AI Enablement programs for Citi, JPMorgan, Google, Microsoft, and T-Mobile.

Ready for case
study number five?

Two-week diagnostic, fixed-fee. Roadmap + working agentic prototype delivered.

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