Existing users
The product already has customers who will not tolerate a regression.
Solutions / SaaS & Technology
Add AI Without Destabilising The Product
Model-backed features shipped into a live product, behind flags, with cost and quality measured per tenant.
- Every rollout
- Flagged
- Cost visibility
- Per-tenant
- Quality before GA
- Gated
The problem
What Makes This Sector Hard
The constraints that shape every architectural decision we make here.
Multi-tenancy
Cost, quality, and data isolation all have to hold per tenant, not on average.
Unit economics
A feature that loses money on power users will not survive contact with growth.
Team capacity
The roadmap promised AI, but nobody on staff has shipped it before.
What we build
Workflows That Earn Their Keep
The highest-volume, lowest-judgement work first. That is where automation pays.
In-product assistants
Grounded in the customer's own workspace data, scoped by their existing permissions.
Semantic search
Replace keyword search with retrieval that understands the domain vocabulary.
Content generation
Drafting features with quality gates and clear edit paths before anything is published.
Usage analytics
Per-tenant cost and quality dashboards so pricing decisions rest on data.
Tooling
Typical Stack For This Work
- Next.js
- TypeScript
- PostgreSQL
- Redis
- Vercel
- Anthropic
Get started
Let's Build It, Together
Tell us what you are trying to ship. We will tell you the three shortest paths to it, and which one we would actually take.