Index/ What Got Built
The Full Portfolio

What Got Built

AI platforms, evaluation engines, governed legal systems, voice pipelines, workflow automation and 132 visual explainers — six domains, all deployed to production.

Production platforms
6
AI agents built
50+
Tests passing
1,050+
Visual explainers
132
Deployments
10+
API endpoints
100+
01

AESOP Transformation OS

Full-lifecycle agent development platform — discover, design, build, evaluate, repair, track. The evaluation engine that later powered Legal-OS’s Harvey monitoring layer.

The hardest problem in AI: how do you evaluate an agent when the agent cannot be trusted to self-assess? Twenty-plus specialised evaluators each score one dimension, then a programmatic engine applies weighted tiers, veto rules and certification levels. No LLM self-assessment.

50 agents  ·  75 API routes  ·  76 migrations  ·  ~990 tests
FastAPI + Supabase + Celery · Next.js 16 · Fly.io + Vercel

Cave of Shadows, the Hydra, Bias Probe, Sentinel, Forge. Hard veto at 75.

02

Legal AI Operating System

A governed platform for building, deploying, measuring and independently evaluating AI across the legal enterprise.

Five layers — knowledge, governance, functions, operations, org model. The breakthrough is independent Harvey evaluation, ported from AESOP and adapted for legal outputs. The newest layer is legal-engineer verification: every filing cite-checked against real case law via Descrybe.

10 functions  ·  15 migrations  ·  77 tests  ·  9 guides
RLS client isolation · ABA 512 ready · legal.sickofancy.ai

Harvey can’t grade its own homework. Legal-OS does.

03

Strategic simulations

Two multi-agent simulations that turn “what does AI transformation actually look like” into concrete, repeatable, falsifiable answers — one about the economics, one about the change process.

An AmLaw 100 firm adopts AI across sixteen sprints and pricing decides everything: hourly billing makes AI a net loss, alternative fee arrangements make the same AI a net win. Same tool, same people, same adoption. Alongside it, two identical copies of one insurer run through organic discovery versus traditional change management — same hurricanes, same attrition, only the change process varies.

16 sprints  ·  2 tracks  ·  30 tests  ·  seeds 42 + 7  ·  deterministic

Design drives adoption. Discovery drives outcomes.

04

SuperAssistant, TSE & TBG Automations

Voice interview pipeline, email automation and workflow orchestration for a consulting firm — serverless across Railway, Supabase and ElevenLabs.

Multi-tenant agent orchestration with structured output pipelines and vector-search knowledge bases. Serverless voice interviews with branching question flow, real-time transcription and analysis. Plus the operational layer: cohort automation, Gmail triage, ecosystem mapping, and Walter — a fully client-owned assistant.

39 API route files  ·  Railway + Supabase + Cloudflare  ·  CI/CD

Manual workflows, turned into pipelines.

05

132 visual explainers

Self-contained HTML pages — architecture diagrams, maturity models, process maps, audit reports, platform showcases — spanning every project.

30 AESOP  ·  19 Legal OS  ·  6-stage Monday pipeline  ·  TBG audits

No frameworks. No build step. Renders instantly.