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CAPABILITIES

One Delivery Standard, Start to Finish.

Every engagement draws from the same practice areas — scoped, audited, and shipped to production, not left as a demo.


AI Strategy & AI-tecting

A fixed AI readiness assessment, use-case prioritization, and a phased roadmap — before any code.

AI readiness assessment

Agentic Workflow Engineering & Orchestration

Deterministic finite state machines, human-in-the-loop approvals, full audit logs.

Finite state machines

Quantitative FinTech Pipelines & Real-Time Risk Engines

Sub-millisecond ingestion, Greeks drift tracking, proven on myMTree.

Real-time risk

Private LLMs & Enterprise RAG Systems

Built on Claude, VPC-isolated, SOC2/GDPR-aligned.

VPC-isolated

Cloud Infrastructure Modernization & DevOps

Event-driven microservices, zero-downtime migrations.

Zero-downtime

Delivery, Governance & Improvement

Deployment doesn't end the engagement — audit trails, drift monitoring, and certification evidence stay on.

Model-drift monitoring

AI Strategy & AI-tecting

Proven before it's built, not after a sprint reveals the gap

Every engagement runs on the same discipline as The Harness Framework: prove the use case is worth building before scope grows. That means a fixed AI readiness assessment against the business objective, a use-case prioritization matrix so effort goes where it pays back, and a phased transformation roadmap — the architecture decisions get made up front, not discovered mid-sprint when a constraint nobody scoped for shows up.

AI readiness assessmentUse-case prioritizationTransformation roadmap

Agentic Workflow Engineering & Orchestration

Deterministic, not improvised

Multi-step autonomous LLM agents backed by deterministic finite state machines, human-in-the-loop approvals, and full transaction audit logs. An agent's next move is always a known state transition — never a fresh guess from the model.

Finite state machinesHuman-in-the-loopAudit logs

Quantitative FinTech Pipelines & Real-Time Risk Engines

Proven on our own product, not just a client's

Sub-millisecond data ingestion, real-time portfolio health monitoring, Greeks drift tracking, and automated risk firewalls. This is the exact discipline behind myMTree, the trading platform we built and operate ourselves.

Real-time riskGreeks drift tracking

Private LLMs & Enterprise RAG Systems

Built on Claude, not a public chat endpoint

Built on Anthropic's Claude models, deployed VPC-isolated with tenant-scoped retrieval pipelines, SOC2/GDPR-aligned data handling, and real vector indexing.

VPC-isolatedSOC2 / GDPRVector indexing

Cloud Infrastructure Modernization & DevOps

Held up in production, not in a slide

Next.js and Postgres monorepos refactored into resilient, event-driven services; zero-downtime database migrations; deployment pipelines running on pm2 and nginx that we've watched hold up in production.

Event-driven microservicesZero-downtime migrations

Delivery, Governance & Improvement

Shipped, then kept honest

Deployment is a milestone, not an exit. We manage the transition from sandbox to production with change management and team training built in, then stay on for governance: safety protocols, model-drift monitoring, audit trails, and certification evidence for regulated industries. The same discipline that governs myMTree's live risk engine governs every engagement we deliver — iterative improvement is a line item, not an afterthought.

Change managementModel-drift monitoringAudit trailsCertification evidence