Every SaaS product launching in 2026 has an AI story to tell. Most of them shipped their first version without one, then tried to paste an AI feature on top months later. The result: cosmetic AI that doesn't actually change how the product works. We build SaaS applications where AI is a core architectural element — where the product is genuinely better because AI is woven into every layer, not an afterthought.
What AI-native SaaS means
AI-native SaaS has three properties that bolted-on AI never quite achieves: the onboarding is smarter (users get set up in minutes via AI instead of hours of manual configuration), the core workflow is dramatically faster (tasks that took 10 clicks take 1 prompt), and the data feedback loop compounds (every user interaction makes the product better for everyone else). Getting all three requires designing with AI from day one.
SaaS products we build
B2B Vertical SaaS
Industry-specific SaaS for legal, healthcare, logistics, real estate, accounting, or architecture firms — with domain-trained AI models and workflows tuned to the vertical.
Internal Tools SaaS
Single-tenant or multi-tenant internal platforms for enterprises — HR tools, operations dashboards, process automation platforms. AI agents built in from the start.
Productivity SaaS
Document/content/workflow tools — AI writing assistants, research agents, document processing pipelines, decision-support systems, knowledge management platforms.
AI-Backed Consumer SaaS
Consumer-facing applications where AI is the differentiation — from AI tutors to financial co-pilots to creative tools. Multi-model orchestration, chat UX, real-time streaming.
Our full-stack SaaS capabilities
We cover the entire SaaS product lifecycle — not just the frontend, not just the AI model, but every layer in between that makes a production SaaS actually work.
UI & UX
React, Next.js, Vue, or React Native. Design system, component library, responsive layouts, real-time UI with streaming, dark/light modes. AI-first UX patterns — chat bubbles, inline agents, context-aware suggestions.
API & Infrastructure
FastAPI, Node.js, or Go. Postgres + vector DB hybrid, Redis caching, BullMQ or Temporal for jobs. Deployed on AWS, GCP, or your preferred cloud with infra-as-code.
Model orchestration
LangGraph, DSPy, or CrewAI for multi-agent workflows. Vector RAG over your knowledge base. Fine-tuned models where the domain demands it, off-the-shelf where general-purpose works.
Auth, billing, analytics
Clerk / Supabase / Auth0 for auth and SSO. Stripe for subscriptions, trials, usage-based billing. PostHog / Mixpanel for product analytics. SOC 2 / GDPR / DPDP / HIPAA where required.
Observability
Sentry, Grafana, OpenTelemetry. Per-tenant token usage, cost tracking, hallucination rate, intervention rate — metrics that matter for AI SaaS but most teams forget to build.
Deploy & scale
CI/CD pipelines, zero-downtime deploys, multi-region where needed, autoscaling GPU inference for AI workloads, cost optimization to keep unit economics healthy.
Our SaaS engagement model
Building a SaaS isn't a 6-week project. We typically engage one of two ways:
- Embedded build team (3–9 months) — 1–3 of our engineers work alongside your team to ship the MVP and first two major versions. You own the code, the infrastructure, and the IP end-to-end.
- Technical co-founder support (ongoing) — for early-stage founders, we operate as a technical partner through your first 12–18 months. Architecture decisions, hiring support, product review. Equity + fee arrangements considered for the right fit.
What we don't do
- We don't build WhatsApp-wrapper SaaS. If your product is a thin wrapper over OpenAI with a subscription page, you don't need us. You need 2 weeks with a freelancer.
- We don't take equity-only deals. Our best clients pay cash plus equity. Equity-only signals misaligned incentives.
- We don't work on ideas that haven't found at least 10 paying customers willing to pre-commit. Product-market fit evidence required before we invest our senior team's time.
Pricing shape
SaaS engagements start at ₹12–30 lakh (USD 15K–36K) for MVP-to-launch builds, scaling with complexity. Ongoing retainers for embedded teams run ₹8–25 lakh/month (USD 10K–30K/month) depending on team size and stack. All engagements include source code ownership, IP transfer, and knowledge transfer clauses — you end the engagement with a system your own team can operate.