Put AI to work.

Depends on the job. We evaluate models based on your use case, budget, privacy requirements, and latency needs, not brand loyalty. Most tasks: Claude or GPT-4. Privacy-critical or self-hosted: open-source (Llama, Mistral). We'll explain the trade-offs clearly so you understand the choice.

We build guardrails into every automation: grounding in your data (RAG), confidence scoring, fallbacks to humans on low-confidence answers, and full logging so you can audit later. Expect ~95%+ accuracy on well-defined tasks with proper scoping.

That's exactly how we recommend working. Pilot one use case (e.g., support chatbot grounded in your FAQ), prove it out, then expand. We don't sell platform rewrites or "AI transformations", we ship one useful thing, then more.

You do. Your data stays in your infrastructure (or at the model provider, never shared). Prompts, eval sets, and custom training data are yours. We don't train on your data or share it, and we'll set up contracts with model providers that match.

We ground responses in your actual data (not the model's general knowledge), set confidence thresholds, and surface sources on every answer. For high-stakes use cases (legal, medical, financial), we add human review loops before publishing.

Yes. Most AI automations slot in alongside existing systems rather than replacing them. We'll connect to your databases, CMS, support tools, etc., and the AI layer sits on top, not a rip-and-replace.

Often not at first, and that's fine: AI answers are only as good as the data behind them, so a focused cleanup or pipeline phase frequently comes first. That's exactly what our data and analytics service covers, and doing it once serves both the AI and your reporting.