Retrieval-augmented generation
Ground LLM responses in your own knowledge base. We build the ingestion, chunking, embedding, and retrieval pipeline so answers are accurate, citable, and current.
Add AI to your existing product without rebuilding it.
Embed LLMs, RAG, and intelligent agents into the apps you already run.
Ground LLM responses in your own knowledge base. We build the ingestion, chunking, embedding, and retrieval pipeline so answers are accurate, citable, and current.
Models that take action: query databases, fill forms, send emails, call your APIs. Built with tool-use, careful permissions, and observable execution.
In-product copilots, customer-facing support bots, and internal helpdesks that actually know about your business and stay in your brand voice.
Output filters, jailbreak resistance, PII scrubbing, and offline evals that run on every prompt change so quality never regresses.
Streaming responses, caching, smart model routing, and prompt optimization. We track per-request cost so your AI bill stays predictable.
Salesforce, HubSpot, Notion, Slack, your custom backend. We integrate where your team already works rather than building yet another tool.
Find the workflows where AI moves the needle on revenue, retention, or cost. Skip the rest.
Working demo on real data within a sprint. Validate quality and economics before committing to a build.
Auth, logging, evals, fallbacks, rate limits, monitoring. The boring stuff that decides whether your AI ships or stays a demo.
We instrument every output, run weekly evals, and tune prompts/models against real usage. AI products get better; static ones decay.
Depends on your task, data sensitivity, and budget. We benchmark options against your actual workflow and recommend based on quality, cost, and latency. Frontier models for hard reasoning; smaller fine-tuned models for high-volume classification.
No. We use zero-retention API tiers from major providers, or self-hosted models on your own infrastructure for highly sensitive data. Contracts and DPAs cover the rest.
Offline evals on labeled examples, plus production telemetry: thumbs-up/down, regeneration rate, downstream conversion. We build the eval harness as part of every engagement.
Inference cost varies wildly by use case. A customer-support chatbot might run $200/month at low volume; a document-processing pipeline might run $5,000. We model this upfront so there are no surprises.
Custom software for SMEs, built with time-proven technology.
Bespoke business applications, internal tools, and ERPs tailored to how your company actually works.
Marketing sites, SaaS, and web apps that load fast and convert.
Fast, accessible, SEO-ready web applications built on the modern stack.
A CRM that fits how your team actually sells.
Custom CRMs, HubSpot and Salesforce integrations, and sales-process automation.
Send us a short brief. We reply within one business day with a recommended next step, an honest range, and the name of the person who would lead the work.