Service · 02
AI Engineering & Automation
A decade of building well-architected AI and automation solutions, secure in your cloud or on-prem. We deliver working prototypes in days on a modern technology stack, then harden them to production: scalable, cost-optimized, and built to last.
01 — Proof of Concept
Working software in weeks, so you decide with evidence.
Proof-of-Concept Build
A production-ready prototype against your real data and workflow: document intelligence, agentic automation, or knowledge search — scoped to prove (or disprove) the business case fast.
AI Governance Rapid Assessment
A focused audit that pairs with any build: where your current AI use stands against NIST AI RMF, and what to fix first.
02 — Architecture & Solution Design
The blueprint before the build, designed by engineers who stand behind it.
Solution Architecture & Design
End-to-end technical designs for AI systems: data flows, model selection, integration points, security boundaries, and cost models — ready for your team or ours to build.
Technical Solution Development
Custom development against an agreed architecture — APIs, pipelines, integrations, and AI features delivered into your existing stack with tests and documentation.
03 — Websites, Dashboards & Analytics
The digital basics for small and midsize businesses, with AI inside.
Business Websites
Fast, modern, accessible websites with AI assistants built in — lead capture, booking, and customer Q&A grounded in your real pricing and policies.
Dashboards & Analytics
Executive dashboards and growth analytics with an AI analyst on top — anomaly detection, plain-English answers, and KPIs your team will actually open. Browse 15 concept designs in the showcase.
04 — Platforms & Systems
The systems behind our case studies, built for your data and your rules.
RAG Platforms & Knowledge Search
AI-powered Q&A and search over your documents and data — hybrid retrieval, contextual chunking, and faithfulness evaluation, the same architecture as DOXA.
MCP Servers & AI Connectors
Give ChatGPT and Claude live, governed access to your systems and data sources — we've shipped six MCP servers with 50+ tools, including ContractsHub.
AI Agents & Orchestration
Multi-step agents with supervisor patterns, LLM judges, and quality gates — automation that checks its own work before it reaches yours.
Process Automation
Document processing, data extraction, email triage, meeting summaries, and report generation — the unglamorous wins that pay for everything else.
Full System Build
Complete end-to-end AI systems through production deployment, with six months of support and full knowledge transfer included.
How we build
Discover → Prototype → Validate.
Phase 1
Discover
Understand the workflow, the data, and the constraint that actually matters. Define what success looks like in numbers.
Phase 2
Prototype
Build the smallest system that proves the value against real data — usually 4–6 weeks to working software.
Phase 3
Validate
Evaluation gates, user testing, and governance review before anything scales. Ship it, measure it, then expand.
Capabilities
Every capability, backed by something shipped.
RAG Systems & Retrieval Engineering
Hybrid BM25 + vector retrieval with RRF and cross-encoder reranking in 4 shipped systems; contextual chunking; faithfulness verification ensembles (NLI + LLM judge); 1.15M chunks in production.
MCP Server Development
Six MCP servers built with FastMCP — two deployed to Azure behind APIM gateways with auth and rate limiting. 90+ tool production surface; stdio and Streamable HTTP transports.
AI Agents & Orchestration
LangGraph supervisor/specialist topologies with human-in-the-loop interrupts; autonomous self-improvement loops with budgeted retries; multi-agent architecture gated by independent LLM judges.
LLM Evaluation & Quality
RAGAS-style eval harnesses wired into CI as regression gates; golden-set testing; LLM-as-judge with multi-axis scoring and majority voting; 4-model prediction arena scored against real market outcomes.
AI Governance & Compliance
Vice Chair of a federal AI Governance Board; former Chief AI Officer. Built working software for OMB M-25-21, EU AI Act, NIST AI RMF, ISO 42001, HIPAA, FINRA, CMMC — crosswalks, risk registers, audit evidence.
Data Engineering at Scale
47 ingestion pipelines moving 30M+ rows; autonomous daily refresh orchestration with quality assertions and anomaly alerting; PostgreSQL + pgvector schema design shared across four products.
Cloud AI Architecture (Azure-first)
Azure Container Apps, API Management, Key Vault, Entra ID, Azure OpenAI, AI Search, Cosmos DB — production deployments that scale to zero and cost almost nothing idle. AWS (Bedrock) and multi-cloud capable.
Multi-Provider LLM Engineering
Claude, GPT, Gemini, Grok in production with structured outputs, fallback chains, prompt caching (~90% eval cost reduction), batch APIs, and per-provider cost guards.
Have a workflow worth automating?
Bring us the problem and a sample of the data. We'll scope a 4–6 week proof of concept with success criteria you define — and tell you up front if it isn't worth building.