Not a vendor.
A team you subscribe to.

Your ingredients

Your team, your data, your workflows, your compliance requirements. These don't change. They're the foundation.

Our heat

Fine-tuned AI models, engineered pipelines, deterministic validation. Purpose-built for your specific operations.

Better together

The same team, doing what they do best — with AI handling the repetitive, time-consuming work that slows everything down.

Cloud AI is a liability

Sending borrower data, patient records, or legal documents to third-party servers isn't just risky — in regulated industries, it's a compliance violation waiting to happen.

Generic tools, generic results

Copilot and ChatGPT are built for everyone — which means they're built for nobody. Your mortgage workflows, production schedules, and contracts need AI that speaks your language.

Enterprise AI ignores you

Microsoft and Salesforce build for Fortune 500. If you have 8 employees and a real operational bottleneck, nobody's building for you. Until now.

Orders arriving as unstructured email and inventory tracked by hand, replaced by a pipeline that reads the email, drafts the invoice into QuickBooks, and holds anything uncertain in a review queue a person clears. Demand forecast per SKU, purchase orders drafted automatically.

One platform for every moving piece of a shoot — crew, cast, travel, documents, budgets, accounting. AI reads receipts, generates ops orders, and flags when a job trends over budget.

Weekly site reports arriving as PDFs over WhatsApp, turned into a structured investor update, emailed to the investor list and published to a portal without anyone retyping anything. Investors ask questions in a chat grounded only in the actual updates.

Clinical charting and billing, architected so patient data is never used for training and audio never persists. HIPAA and 42 CFR Part 2 by architecture, not by promise — the audit trail is a byproduct of where the system runs.

Contracts drafted from your firm's own executed agreements. Multi-pass validation checks every clause, date and party name. Full version history. Attorney-client privilege preserved by architecture.

Lead qualification by text, around the clock — collecting balance, rate, term, address and value so loan officers spend their time on the leads that are actually ready. Built to Freddie Mac's AI governance requirements.

Neither. A vendor sells you their product and an agency bills you by the hour. We are a fractional AI team you subscribe to — one contract, one number, and a team that finds the work your people do by hand, builds the system that does it, and then keeps it running. Sized to fit: a five-person office and a hotel development fund do not get the same system.

Typically four to six weeks to the first shipped workflow. Week 0 is the assessment. Then a written scope you sign off on before anything is built — nothing gets made from a verbal request that drifts later. Then the build, then shadow mode running alongside your people so you can compare, then live. After that, the part most vendors skip: hosting, monitoring, on-call and enhancements, all inside the same monthly number.

Live systems today in B2B distribution and in real estate development, with production platforms in build and conversations running in healthcare, corporate law and mortgage lending. The through-line is not the industry — it is high-volume, rule-bound work being done by hand in a business of 5 to 30 people, where the owner makes the decision. Regulated industries are a specialty because on-premise deployment is something almost nobody else offers.

Cloud when cloud is fine, and on hardware in your building when it is not — and we build that hardware ourselves: spec, assembly, full-disk encryption, install and support. On-premise means the models run on a machine in your office, no cloud APIs, no third-party training on your data, and conversation logs and audit trails stored locally for regulatory review. Either way your data, templates and know-how stay yours and stay exportable.

Every AI response passes through a JSON validator and deterministic rules engine before reaching anyone. The model never acts unsupervised. When the validator catches an issue, it falls back to a templated response. Every failure is logged and becomes training data for the next version — the system gets smarter over time.

Qwen 2.5, Llama 3.3, Mistral, and DeepSeek — whichever best fits your use case. All run locally on consumer-grade GPUs. Fine-tuned on your data using QLoRA. No API costs, no vendor lock-in, no dependency on OpenAI or Google.

After the initial term it is 60 days' notice, no exit fee, and a full export of your data. We own the engine; you hold a perpetual licence to your instance. On-premise, it keeps running on your hardware — what ends is the support: patches, model updates, monitoring and on-call. In the cloud we are the ones paying for hosting, so that ends with the retainer and we either migrate it into your own accounts or hand it over. If you would rather keep running it yourself, the handoff is a fixed price you choose to buy: documentation, infrastructure, training for your people, and thirty days of support while they take over.

The opposite. We build around the workflow you already have, not the other way around. Your team keeps doing what they do — the system takes the repetitive, rule-bound parts. And it runs in shadow mode alongside your people first, so you can compare its output against theirs before anything actually changes.

One monthly number — $4,500, $8,500 or $15,000 depending on how much capacity you need — with no setup fee and no hourly billing. Most people start with the AI Readiness Assessment: two weeks, $3,500 fixed, credited in full against your first month if you go ahead. You get the written document either way — the three highest-value automatable jobs in your business, what we would build, and an honest answer if none of it is worth doing yet.