MVP to product-market fit
Fast, honest iterations on real users — with architecture that survives success.
Services
AI SaaS Product Development
From MVP to multi-tenant scale — product, platform, and go-to-market technical foundations.
- 12 wkstypical MVP-to-market timeline
- 99.9%availability engineered from day one
- 70%+gross margin targets met
Capabilities
From idea to enterprise-grade SaaS
Scalable AI SaaS products for new markets and product lines.
Multi-tenant AI
Tenant isolation, per-customer knowledge and BYO-cloud options for enterprise buyers.
Billing and metering
Usage tracking wired to Stripe and your pricing model from the start.
Reliability engineering
SLOs, failover and observability that keep the product up as it scales.
How we deliver
SaaS discipline plus AI engineering
AI SaaS fails two ways: classic SaaS mistakes, or AI-specific ones. We've shipped enough of both categories to prevent them.
Velocity
Real users in weeks, not quarters
A deliberately thin first slice on production-grade rails: auth, billing, observability and eval gates from sprint one, so iteration speed never trades against stability.
- Production rails from the first deploy
- Weekly releases with feature flags
- User feedback loops instrumented natively
Invoice exception workflowRunning
✓Extract invoice fields1.1s
✓Match against PO0.6s
Resolve mismatch with agentrunning
·Post to ERPqueued
AI core
The intelligence layer, done right
Model routing, retrieval, evals and cost controls built as product infrastructure — quality you can prove to customers and costs you can price against.
- Eval-gated releases for AI behavior
- Model routing for cost and quality per feature
- Per-tenant knowledge with hard isolation
Incoming taskcomplex reasoning · 12k ctx
Router
Claude Sonnetquality-critical
GPT-4.1fallback
Llama 70Bhigh volume · low cost
FailoverA/B evalsCachingBudgets
Scale
Ready for the enterprise deal
SSO, audit logs, residency options, admin controls and security documentation — prepared before procurement asks, so your biggest deal doesn't stall in review.
- Enterprise auth and admin consoles
- SOC 2-aligned controls and evidence
- Load-tested to your growth scenarios
✓PII detected & redactedenforced
✓Answer grounded in sourcespassed
✓Role-based data accessenforced
✕Out-of-scope tool callblocked
SOC 2GDPRAudit logHITL
Use cases
What founders build with us
Vertical AI SaaS
Domain products for legal, health, logistics and finance.
AI-first tools
Products where the model is the core experience.
Prototype hardening
Demos re-engineered into sellable products.
Enterprise pivots
SMB products upgraded for enterprise buyers.
Usage-based pricing
Metering and billing aligned to AI costs.
Scale crises
Products stabilized under sudden growth.
Delivery
How we engage
Flexible models — from strategy sprints to dedicated pods — with clear phases, quality gates, and ownership through production.
- Clear delivery process
- Senior engineering talent
- Security built in
- Long-term capability transfer
-
1
Align
Goals, constraints, success metrics and stakeholders.
-
2
Design
Architecture, delivery plan and risk controls.
-
3
Deliver
Build, integrate, harden and launch.
-
4
Operate
Monitor, optimize cost and continuously improve.
They told us which half of our spec to cut — and they were right. We hit the market in eleven weeks and closed our first enterprise logo with the security page already written.
Works with your stack
The stack we ship on
Boring where boring wins, modern where it matters.
- Next.js
- TypeScript
- Python
- Postgres
- Redis
- Stripe
- Anthropic Claude
- OpenAI
- Pinecone
- AWS
- Vercel
- Datadog
FAQ
Common questions
Fixed price or time and materials?
Fixed-scope phases with demoable milestones. You know the cost of each phase up front and can exit at boundaries — incentives stay aligned.
Who owns the codebase?
You do, from the first commit — your repos, your cloud accounts, IP assigned contractually. We're a build partner, not a dependency.
Can you help us hire the team that takes over?
Yes — we regularly support hiring loops and onboard your engineers during the build so handover is a merge, not a cliff.
What if our idea needs to pivot mid-build?
Two-week cycles absorb pivots; we re-plan openly and re-cut scope. What we won't do is pretend the original estimate still holds.
Next step
Build a SaaS the market pays for
Feasibility sprint first — know what's real before you fund the build.