AI Solutions & Development
Custom AI systems built in your repository, on your cloud, from the first commit. You own 100% of the code and IP.
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Build it, ship it, hand over the keys. Production systems integrated with the software you already run — governed, monitored, documented, and owned by you.
- Generative AI ApplicationsLLM-powered products and internal tools
- AI ChatbotsCustomer and employee-facing conversational systems
- AI AssistantsDomain assistants embedded in real workflows
- AI AgentsMulti-step autonomous workflows with guardrails
- LLM ApplicationsPrompt systems, structured output, orchestration
- RAG SystemsPermission-aware, cited retrieval over your content
- Machine LearningClassification, ranking, recommendation, clustering
- Predictive AnalyticsDemand, churn, risk, pricing, maintenance
- Computer VisionImage and video analysis, inspection, OCR pipelines
- Natural Language ProcessingExtraction, classification, summarization
- AI AutomationDocument and workflow automation end to end
- AI-Powered SaaSProduct engineering for AI-native applications
- API IntegrationsConnecting AI to the systems that run the business
Engineering standards
What we commit to in writing.
- —Everything lives in your repository, under your license, from day one.
- —Infrastructure as code. No consultant-configured console clicks.
- —Evaluation suites ship with the feature and run in CI on every change.
- —Every AI decision touching a customer is logged and reversible.
- —Human-in-the-loop by default on anything financial, clinical, or legal.
- —Documentation and a recorded handover are in scope, not a change order.
Accelerators
Every serious AI firm has a library of reusable internal components. Ours exist to cut the boring 40% of a build — the scaffolding, the plumbing, the evaluation harness — so the budget goes into the part that is specific to you.
- RetrievalGrounding KitChunking, embedding, re-ranking, citation enforcement, and a retrieval evaluation harness. Turns "we want to search our documents" into a measurable baseline in days rather than weeks.
- AgentsAgent FrameTool registry, permission scoping, human approval gates, step-level tracing, cost and latency budgets, and a rollback path. The guardrails are the starting point, not the retrofit.
- QualityEval BenchGolden datasets, automated evaluations in CI, regression gates on every prompt and model change, and drift monitoring. The component most teams skip and then wish they had.
- DocumentsDoc PipelineClassification, extraction, validation, and confidence-based routing — straight-through where the model is sure, escalated to a person where it is not.
- GovernanceControl PackModel inventory, risk tiering, review-board templates, audit logging standards, and an acceptable-use policy your employees can actually follow.
- PlatformGround WorksInfrastructure-as-code baselines for AWS, Azure, and GCP — identity, networking, secrets, observability, and CI — so nothing is configured by hand in a console.
How this works commercially. Accelerators are not products we license to you and they carry no separate fee. They are delivered into your repository under your license along with everything else, and you are free to modify or discard them. We name them because "we have reusable components" is a claim; naming them is an invitation to ask what is in them.
Bring us your AI challenge.
A free 45-minute triage session. You leave with a written problem statement whether or not we work together.