AI Integration
From chat to RAG to agents — practical AI that moves your product forward.
Most AI features fail because they're a demo, not a product. We build AI that earns its place in your app: grounded in your data, measurable, safe, and shipped behind the same engineering bar as the rest of your stack.
— Capabilities
What we build.
Conversational features wired into your product, your tone, your data.
Search and answer across docs, tickets, transcripts — with citations users can trust.
Multi-step automations that take real actions, with humans in the loop where it matters.
We measure quality, prevent drift, and keep costs under control as you scale.
— Deliverables
What you receive.
- AI feature scoping & success metrics
- Model selection & cost plan
- Prompt + evaluation suite
- Vector / hybrid search pipeline
- Streaming UI components
- Logging, observability, safety filters
- Production deployment & runbook
— Stack
Tools we trust.
Fixed scope, fixed price. Larger projects scoped on request.
— Timeline
How it ships.
Use case, data audit, model & cost plan, success metrics.
First working feature behind a feature flag, internal evals.
Streaming UI, safety, monitoring, cost guardrails.
Ship to users with dashboards and a runbook.
— Deep dive
AI integration: shipping practical AI into real products, not demos
Most AI features fail because they were built as demos: a clever prompt, a flashy chat bubble, and no thought given to data, evaluation, cost or what happens when the model is wrong. We build AI features the same way we build any other product surface: grounded in your actual data, measured, safe, and shipped behind the same engineering bar as the rest of your stack.
Our AI work spans four practical patterns. Conversational assistants wired into your product with your tone and your data. Retrieval-augmented generation (RAG) over your docs, tickets, knowledge base or transcripts — with citations users can verify. Agents and multi-step workflows that take real actions across your systems, with a human in the loop where it matters. And background AI features — classification, extraction, summarization, ranking — that quietly make your existing product smarter.
We choose models pragmatically. OpenAI, Anthropic, Google Gemini, open-source via the Lovable AI Gateway — whichever combination gives you the best quality, latency and cost for your specific use case. We benchmark them on your real data, set up evaluations to track quality over time, and build cost guardrails so a viral moment doesn't become a viral invoice.
Behind every AI feature we ship, you get the unsexy but essential parts: logging, observability, safety filters, rate limiting, fallback paths, prompt versioning and a runbook. So when something changes — a model deprecation, a price change, an unexpected input — your team knows exactly what to do, and your users barely notice.
AI integration FAQ
- Which AI models do you use?
- We are model-agnostic. We pick the right combination of OpenAI, Anthropic, Google Gemini, or open-source models — based on your quality, latency, cost and privacy constraints. We benchmark on your data before recommending.
- Can the AI use my private data?
- Yes — securely. We build RAG pipelines that retrieve from your knowledge base, docs, database or transcripts and ground the model's answers in them, with citations. Your data is never used to train public models.
- How do you control AI cost?
- Caching, smaller models for cheap tasks, larger models only when needed, prompt compression, retrieval to keep context small, per-user and per-day rate limits, and dashboards so you always know what is being spent and on what.
- How do you handle hallucinations?
- We ground answers in your data via RAG, force citations, validate outputs against schemas, run evaluations against a labelled set, and add safety filters and guardrails for high-stakes flows.
- Is on-device or local AI possible?
- Yes. For privacy-sensitive use cases we can deploy open-source models in your own cloud or even on-device, and design hybrid flows where sensitive steps stay local and only non-sensitive steps hit external providers.
Let's build your ai integration.
Tell us what you need. We reply within 24 hours.