Service
AI-Integrated Solutions
We embed large language models, retrieval, and intelligent automation into your products—not as demos, but as production features with guardrails, observability, and UX built for your users. OpenAI, Anthropic, xAI, and modern vector stacks, delivered through a unified model layer that makes switching providers a configuration change, not a rewrite.
How we ship production AI
- TanStack AI
- Multi-model framework
- xAI · OpenAI · Anthropic
- Frontier Providers supported
- RAG
- Vector search
- UI
- Streaming, Modern UIs
Capabilities
What we build
LLM Interfaces & Copilots
Chat, command palettes, and in-app assistants grounded in your data, streaming responses, citations, and fallbacks when models are uncertain.
Semantic Search & RAG
Vector indexes, chunking strategies, and retrieval pipelines so answers pull from your docs, not the public internet, with relevance tuning and eval loops.
Intelligent Automation
Classify, extract, route, and summarize at scale, connecting models to your CRM, ticketing, or ops tools with human-in-the-loop where it matters.
Multi-Model Routing with TanStack AI
TanStack AI gives us a unified adapter layer across xAI Grok, OpenAI GPT, Anthropic Claude, and beyond so the right model for each task is a config swap, not a rewrite.
Data & Vector Infrastructure
Postgres + pgvector, managed vector DBs, embeddings pipelines, and sync jobs that keep knowledge fresh as your content changes.
AI-Native UI Components
Streaming UIs, diff views, suggestion chips, and safe-edit patterns, so AI feels like part of your app, not a bolt-on iframe.
Technology
Our stack
- TanStack AI
- TanStack Query
- xAI API
- OpenAI API
- Anthropic API
- Azure Foundry
- React
- TypeScript
- Node.js
How We Work
Our process
AI projects fail without clarity on data, risk, and success metrics. We start there.
We define the job-to-be-done, PII boundaries, and what “good” looks like, including offline eval criteria before we wire up production.
Source mapping, chunking, metadata, and access control, so retrieval is accurate and auditable for your domain.
Thin vertical slice with real APIs and fixtures. We measure latency, cost per request, and answer quality on representative queries.
Rate limits, caching, streaming UX, error handling, and logging, plus red-team prompts for your highest-risk flows.
Feature flags, dashboards, and feedback hooks so you can iterate safely with real usage, not guesswork.
We stay on for model upgrades, eval refresh, and new surfaces, copilots tend to grow once users trust the first one.
Ship real AI
Ready to put models in production?
Bring us your product surface and your data reality. We'll design retrieval, safety, and UX so AI earns trust, not hype.
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