Build AI-powered SaaS that actually ships.
AI receptionists, AI CRMs, AI dashboards, document processing, agentic workflows — we design, build and launch production AI SaaS products for startups, SMBs and modern businesses.
Who this is for.
Founders and operators who want a real AI product, not a chatbot wrapper. You have a use case (or a customer asking for one) and you need a team that can ship the LLM layer, the dashboard, the auth, the billing, the deploy pipeline — without you architecting any of it.
What we hear from teams who come to us.
- Your AI proof-of-concept demos well but won't survive a real customer load.
- Costs are unpredictable — every prompt change moves your unit economics.
- Hallucinations and grounding failures keep blocking your launch.
- You have an OpenAI bill but no product around it.
- Your team is great at one of (frontend, AI, backend) — but not all three.
A production AI SaaS — frontend, backend, AI layer, billing, ops.
AI receptionist / agent
Voice or text, multi-turn, grounded in your knowledge base. Escalation rules to humans baked in.
AI CRM & sales co-pilot
Lead enrichment, call summaries, follow-up drafts, pipeline insights — inside your CRM or as standalone.
Document processing
Extract, classify, summarize, redline — at scale, with citation-grounded output.
AI dashboards
Natural-language queries over your data, with SQL guardrails and explainable results.
Agentic workflows
Multi-step agents with human-in-the-loop checkpoints. Never unsupervised on customer-facing actions.
Multi-tenant from day one
Workspace isolation, per-tenant rate limits, audit logs, SSO, billing — table-stakes for SaaS.
Cost-aware
Per-tenant token budgets, prompt caching, smaller models for cheap paths, fallback chains.
Safety & guardrails
PII redaction, prompt injection mitigation, output validation, abuse detection.
Production observability
Every prompt, response, latency, cost and outcome logged and queryable.
Pragmatic, battle-tested, swappable.
We pick stacks that fit the product — not the other way around. Every project comes with documented architecture, clear deployment, and a path off any tool we choose.
How a ai saas development engagement runs.
AI feasibility
We test the AI path early. Can the model do what you want? At what latency and cost? Cheap before deep.
UX & schema
Product surface designed around the AI capabilities — not bolted on. Schema designed for AI grounding.
Build
Frontend, backend, AI layer, billing, ops. CI/CD from day one.
Eval & guardrails
Eval set built from real prompts. Guardrails tested before launch. Cost regression caught in CI.
Launch & monitor
Day-1 monitoring, on-call rotation, cost dashboards, alert thresholds tuned per tenant.
Common questions.
Ready to start a ai saas development project?
Send us a brief — we'll come back with a tailored estimate inside 48 hours.