Custom AI Engineering

AI Built on
YOUR Data

Not pre-built agents. Not generic tools. Custom AI systems engineered from the ground up — trained on your proprietary data, integrated into your systems, solving your domain problems.

What We Build

Four ways we engineer custom AI for your proprietary data

Fine-Tuned Models

AI models trained specifically on your proprietary data — your industry knowledge, products, customers, and internal processes. Not general language. Your domain.

  • Trained on your documents and data
  • Knows your brand voice and standards
  • Always cites your sources
  • 40-60% accuracy improvement over generic AI

💡 A law firm fine-tuned a model on their case history. Now it drafts and reviews contracts in their specific practice areas.

RAG Pipelines

Your entire knowledge base — contracts, CRM, technical docs, emails — indexed and searchable. Ask any question, get answers grounded in your actual documents.

  • Searches 100s of documents instantly
  • Always cites the source
  • Real-time data, not training data
  • No hallucinations on your data

💡 A manufacturer's field team gets AI-generated repair recommendations from 15 years of service records.

Agentic Workflows

Multi-step tasks completed autonomously in your systems. Research leads, enrich data, draft responses, update records — without human intervention.

  • Multi-step task automation
  • Integrates with your existing tools
  • 0 human approvals needed
  • Completes in seconds

💡 An incident gets triaged, lot-validated, response drafted, and ops notified — all before a human sees it.

Custom AI Employees

AI workers trained on your business that run 24/7 on repeatable work. Researches, drafts, updates, follows up — without constant human input.

  • Handles repetitive tasks continuously
  • Integrates with your tools and systems
  • Reports productivity metrics
  • 20+ hours saved per week

💡 An AI employee reviews field failure tickets, matches incidents to lot traces, and drafts plant-floor updates every morning.

AI Assessments

Before committing to a full project, get a structured evaluation: data audit, workflow mapping, and a written recommendation on what to build first.

  • Data inventory and quality assessment
  • Workflow mapping and AI opportunity sizing
  • Feasibility analysis and build recommendation
  • $2,500 credited toward any subsequent project

💡 A mid-size firm started with an assessment. Two weeks later they had a clear roadmap — and a fine-tuned model in production within 8 weeks.

How It Works

Not a configured tool. Not a vendor platform. Custom engineering for your data.

01

Discovery

We spend time understanding your data, your workflows, and your highest-impact opportunity. Not a pitch — a real assessment.

02

Engineering

We build a custom system around your specific data and environment. Fine-tuning, RAG, agentic workflows — whatever fits your problem.

03

Delivery

We deploy, test, and measure against your specific use cases. You own the system. We measure results.

Industries We Work With

Every engagement is built around your specific proprietary data

Manufacturing & Engineering

Quality inspection, field service, supply chain, predictive maintenance

Data: CAD files, inspection logs, service records, sensor streams

Legal & Compliance

Contract review, case research, document processing, compliance

Data: Case histories, precedents, contracts, regulatory documents

Healthcare & Medical

Clinical documentation, patient records, claims processing

Data: EHR records, clinical notes, treatment protocols

Financial Services

Modeling, reporting, client data analysis, risk assessment

Data: Financial models, client portfolios, market data

Professional Services

Research, document drafting, client knowledge management

Data: Client files, practice area knowledge, internal docs

Ready to Build AI That Knows Your Business?

Generic AI doesn't know your data. Let's talk about building AI that does.