AI Development That Ships to Production
LLM apps, RAG pipelines, AI features, and AI MVPs, built by a senior team that has shipped AI into real products like SmartDecision AI and Slashscore AI, including air-gapped environments.
★ 5.0 on Google AI products in production Senior team since 2017
AI that earns its place in your product
Feature integration, LLM and RAG apps, agents, and AI MVPs. Built, measured, and shipped by a senior team.
AI Feature Integration
Add AI to a product you already have. Search, summarization, classification, drafting, or chat, wired into your existing app without a rewrite.
LLM & RAG Applications
Chat and retrieval over your own data. Vector search, grounding, citations, and guardrails so answers stay accurate and on-topic.
AI MVPs
Validate an AI product fast. We scope the smallest version that proves the idea, ship it in weeks, and measure whether it actually works.
AI Agents & Automation
Agentic workflows that use tools, call your APIs, and take real actions. We automate the manual steps that eat your team's week.
Private & Air-Gapped AI
AI for security-conscious environments. We shipped SmartDecision AI into air-gapped deployments, so model choice, data isolation, and on-prem are familiar ground.
Evals & Quality
AI that ships needs to be measured. We build evaluation sets, track accuracy and cost over time, and stop the demo-that-can't-ship problem.
A transparent path from idea to production
Four phases. Feasibility before code. Evals before launch. Accuracy you can measure, not just demo.
- 01 1–2 weeks
Scope
We pressure-test the use case. Is AI the right tool, what does good look like, and how will we measure it. Outcome: a written plan, feasibility read, and fixed estimate.
- 02 Signed before kickoff
Plan
Model choice, data flow, retrieval strategy, guardrails, and an eval set. Agreed up front so accuracy and cost aren't a surprise after launch.
- 03 Iterative
Build
Working software every two weeks, scored against the eval set each time. We tune prompts, retrieval, and models against real data, not vibes.
- 04 Ongoing
Operate
Monitoring, cost tracking, accuracy regression checks, and model updates as the frontier moves. We stay on as your AI team or hand off to yours.
The kinds of teams we build AI for
AI development is the right call when you need it to actually ship: accurate, fast, affordable, and maintainable past the demo.
Teams adding AI to an existing product
You have users and a working app, and now you need search, chat, or automation that actually helps. We integrate AI without putting your roadmap on hold.
Founders validating an AI MVP
You have an AI idea and need to know if it works before raising or scaling. We ship the smallest honest version fast and measure it against real users.
Companies with strict data or compliance needs
Your data can't leave the building. We've deployed AI into air-gapped, security-conscious environments and design for data isolation from day one.
Teams stuck with a demo that won't ship
The prototype was magic. Production is hallucinating, slow, and expensive. We bring the evals, guardrails, and engineering discipline that get AI to production.
The AI stack we build on
Frontier models fronting a real, maintainable application. Model-agnostic, eval-driven, production-first.
OpenAI / Anthropic
Frontier model APIs, including Claude and GPT. We pick the model per task on accuracy, latency, and cost, not on hype.
RAG & Orchestration
Retrieval pipelines built to ground answers in your data, with citations and guardrails. Custom or framework-based, whichever fits.
Vector Databases
pgvector, Pinecone, or similar. Embeddings, semantic search, and retrieval tuned for relevance and speed.
React / Node / TypeScript
The same product stack we've shipped since 2017. AI sits inside a real, maintainable application, not a notebook.
AWS Serverless / Bedrock
Serverless infrastructure for AI workloads, with private model options when the data can't leave your perimeter.
Evals & Observability
Evaluation sets, accuracy tracking, prompt and cost monitoring. The instrumentation that tells you AI is still working in production.
What teams ask us about AI development
Short, honest answers. If yours isn't here, book a call and we'll answer it directly.
Do you build with OpenAI, Anthropic, or your own models?
// Answer
We're model-agnostic. For most product work we use frontier APIs (Claude, GPT) because they're the fastest path to a quality result. We pick per task based on accuracy, latency, and cost, and we'll move you to open or self-hosted models when data residency, compliance, or unit economics call for it.
We tried an AI prototype and it won't ship. Can you help?
// Answer
This is the most common reason teams come to us. A demo that works once is easy; a feature that's accurate, fast, and affordable at scale is an engineering problem. We bring evaluation sets, retrieval grounding, guardrails, and cost discipline to turn a promising prototype into something you can put in front of users.
Can the AI run in a private or air-gapped environment?
// Answer
Yes. We built SmartDecision AI to deploy into air-gapped, security-conscious environments, so isolated networks, on-prem models, and strict data boundaries are familiar territory. We design data flow and model choice around your constraints from the first week.
How do you stop hallucinations and keep answers accurate?
// Answer
Grounding and measurement. We use retrieval to anchor answers in your data, add guardrails and citations, and build an evaluation set so accuracy is a number we track, not a feeling. Where the model shouldn't guess, we design it to say so.
What does an AI project cost?
// Answer
AI MVPs and feature integrations are fixed-scope, so you get a defined total upfront. Ongoing work (new capabilities, eval maintenance, model updates) runs on a clear monthly retainer. Book a 30-minute call and we'll give you a concrete range based on your use case.
Three ways to work together
Fixed-scope AI MVP, ongoing product team, or senior AI engineers inside your own team. Pick the model that fits your stage.
Fixed-Scope Project
Best for AI MVPs, feature integrations, and proofs of value.
- Defined scope and deliverables
- Fixed timeline and budget
- Signed SOW before kickoff
- Built, evaluated, and launched end-to-end
- 30 days of post-launch support
Dedicated Team
Best for AI products that need an ongoing partner.
- A senior team that's truly yours
- Agile sprints, roadmaps, and demos
- Eval maintenance and model updates
- Flexible scope as your product grows
- Design, engineering, DevOps, and support
Staff Augmentation
Best for adding senior AI engineers inside your team.
- Senior React, Node.js, and AI engineers
- Embedded in your workflow and tools
- Scale up or down on a sprint's notice
- Your process, your tools, your standards
- No long-term lock-in
What else we do
One team, one contract, full product journey.
Got an AI product you want to ship?
Book a 30-minute call with the founders or send a message. We reply within one business day.
Talk to the founders directly
No sales pitch. We'll give you a concrete cost and timeline range on the call.
Tell us about your project
Share what you're building, where it's at, and what you'd like our help with. We reply within one business day.