We build AI features that run in production. Not prototypes. Not demos. Working systems inside real products, used by real people every day.
Start a projectExtract structured data from contracts, invoices, medical records, and legal documents. The system handles formatting inconsistencies, multi-language inputs, and handwritten sections. Not OCR. Actual comprehension of what a document says and means.
Custom assistants trained on your data. Support agents that resolve tickets without escalation. Internal tools that answer policy questions accurately. Customer-facing chat that knows your product catalog. Every answer cites its source so you can verify it.
Replace manual classification, routing, and approval workflows with AI. Insurance claims get triaged. Support tickets get categorized and routed. Leads get scored. Each decision includes a confidence score and an escalation path for edge cases.
Semantic search that understands intent, not keywords. Users find the right answer even when they phrase the question differently every time. Product recommendations based on behavior patterns, not just purchase history.
Generate product descriptions, financial summaries, compliance reports, and marketing copy at scale. Every pipeline includes quality scoring, brand voice validation, and human review checkpoints. No unreviewed content reaches users.
Turn unstructured text into searchable, structured data. Entity extraction from emails and documents. Sentiment analysis on reviews. Deduplication across databases. Pipelines that improve accuracy as they process more data.
OpenAI, Anthropic, Llama, Mistral, and custom fine-tuned models. We pick based on accuracy, latency, and cost for your specific use case. No vendor lock-in.
Vector search with Pinecone, Weaviate, and pgvector. Chunking strategies, embedding model selection, and re-ranking tuned per domain.
Agent frameworks, function calling, chain-of-thought routing. Complex multi-step tasks broken into reliable, testable sub-tasks.
Automated accuracy benchmarks, regression testing on every prompt change, and A/B testing in production. Every model update is validated before it reaches users.
Input validation, output filtering, PII detection, and hallucination scoring. Safety and compliance are features, not afterthoughts.
Model hosting, API gateways, request queuing, response caching, and cost monitoring. The same production standards we apply to every service we build.
We do not pick a model and go looking for problems it can solve. We start with the business result you need and work backward to the simplest technical solution. Sometimes that means GPT-4. Sometimes it means a rule engine and a regular expression.
The first AI feature runs in a real environment by the end of week one. Deployed, monitored, logging every request. Not a notebook. Not a slide deck with accuracy charts. A service your team can call and get a response they can use.
Every AI feature has a defined accuracy target, a latency budget, and a cost ceiling before the first line of code is written. We build evaluation pipelines alongside the feature itself. You always know exactly how well it is working.