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Case 04 07
AI / B2B SaaS MVP build, fixed-window engagement

AI SaaS: MVP build that secured the seed round

Anonymised Early-stage AI SaaS

An early-stage AI SaaS team needed seed-ready MVP development in months — a working multi-service Python/Vue system, not a prototype, credible to institutional investors.

The brief

An early-stage founding team had a sharp product thesis and a short runway. They needed a working MVP credible enough to raise an institutional seed. Not a prototype, but a real multi-service system with the integrations and scaffolding to demo end-to-end.

What we shipped

  • Frontend: Vue application covering the core user flows the demo and pilot customers needed.
  • Backend services: Python and Django microservices for auth, scheduling, and the workers that ran the product's automation logic.
  • Async pipelines: Celery-based worker queues for long-running and scheduled tasks, with the dashboards to monitor them.
  • Third-party integrations: service-level integrations with the external systems the product depended on for its core workflow.
  • Deployment: containerised services on Kubernetes with the CI and configuration to ship safely.

Outcome

The MVP shipped to production within the engagement window and became the product the founding team raised their seed round on, around $1M. After the raise, we handed the system over to the in-house engineering team they hired and ended the engagement cleanly.