PAGE / 03 Work

Strategy 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.

CASE / 01
ClientW. L. Gore × 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.

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
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.

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).

Ready for case
study number five?

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