AI-powered products your users will pay for.
From RAG-based document Q&A to AI copilots and recommendation engines — we build products where AI is the core feature, not a bolt-on sidebar.
ChatGPT proved users will pay for AI. The real opportunity is embedding intelligence so deeply into your product that users can't imagine the old way. We ship AI applications — not demos — with real-time inference, user-specific context, retrieval-augmented generation, and production-grade reliability. Designer and engineer paired daily, just like every other product we build.
Prototype to production
Uptime SLA
+ custom fine-tuned models
Text · image · voice
RAG & document Q&A
Upload any document corpus and ask questions in natural language. We build vector databases, chunking strategies, and citation-backed answers that don't hallucinate.
AI copilots
Context-aware assistants embedded inside your product — not a chat widget tacked on the side. They understand the user's current task and surface the right action at the right time.
Generative features
Draft generation, image creation, code completion, and content rewriting — integrated into your UX so smoothly users think you built the model yourself.
Recommendation engines
User behavior + content embeddings to surface personalized suggestions. Built for latency, not just accuracy — so recommendations feel instant.
Vision & image AI
Object detection, OCR, visual search, and image classification. Process images and video at scale with models tuned for your specific domain.
Rapid prototyping
Validate an AI concept in 5 days with a real prototype using your data. Kill bad ideas fast, double down on the ones that activate users.
Discovery
Map the user problem, audit your data assets, and pick the AI approach (RAG, fine-tuning, agents, or hybrid). Walk out with a one-page AI strategy.
Prototype
Working AI prototype in 1 week using your real data. Test with 5–10 users, measure activation, and decide whether to build the full product.
Production build
Full-stack product with vector DB, inference pipeline, frontend integration, auth, and usage analytics. Weekly demos, production by week 6–10.
Launch & optimize
Soft launch with feature flags, monitor latency and cost per inference, A/B test prompts, and iterate on the model based on real user feedback.
Every engagement ships these.
No upsell games. The full system is in the base scope so you can measure honest ROI from month one.
- AI product strategy + data audit
- Vector database architecture
- Retrieval + inference pipeline
- Prompt engineering framework
- Frontend AI integration
- Usage analytics & feedback loop
- Model eval + safety testing suite
- Launch playbook + scaling roadmap
Which AI model do you use?
We start with GPT-4o, Claude, or Gemini depending on your use case. For high-volume or sensitive data, we fine-tune open-source models and host them privately. No vendor lock-in — we architect so models are swappable.
How do you prevent hallucinations?
RAG with citation grounding, constrained generation, and human-in-the-loop for uncertain answers. We measure hallucination rate as a KPI and optimize it continuously.
What about AI costs at scale?
We design for cost from day one: caching, model routing, prompt compression, and batching. Most products run under $500/month in inference costs at launch.
Can you add AI to an existing product?
Yes. We audit your current stack, identify the highest-ROI AI surface, and embed it without rewriting your codebase. Most integrations ship in 3–4 weeks.
Ship in 6–10 weeks. If we don't pay for ourselves, we work free.
Get a free product architecture review and a custom roadmap. We build web apps, mobile apps, and AI-powered products end-to-end — shipped by a senior team.
Book your intro callZero technical debt. Full IP ownership. Fixed-timeline delivery.