.png)
Research report
The SaaS Playbook Has a Citation Problem
Don't run your tech stack on unverified SaaS myths.
Platform engineering for product companies — tenancy, scale and the controls enterprise buyers ask for.
The work we are asked to do in saas & technology.
The decision that sets cost-per-customer for the next five years.
Performance and cost engineering for the growth you are forecasting.
SSO, audit trails and access control, in place before the deal requires them.
Regional isolation designed before a large customer makes it urgent.
Senior people who join your team rather than run a parallel project.
The numbers behind our saas & technology work
Multi-tenancy decisions made in month three set your gross margin for the next five years. Most teams discover this at the point where a large customer asks for data residency and the honest answer is a rewrite. It is a commercial decision wearing an architecture diagram, so we model cost-per-customer alongside the architecture and put both in front of whoever owns the P&L.
the scale we have run
what the model was worth
products shipped
countries where our software runs
Engagements in saas & technology, described rather than named.
It depends on what your customers will demand and what your margin can carry. Shared tables are cheapest and need rigorous tenant-aware access control; separate schemas or databases isolate better and cost more to operate. The decision is commercial as much as technical, and it is expensive to reverse.
That request is the moment tenancy decisions made in month three present their bill. The honest answer depends on whether your data layer can be partitioned by region without rewriting the application. We assess that first, because the answer decides whether this is weeks of work or a quarter.
SSO, granular permissions, audit trails, data residency and a security questionnaire you can answer without a scramble. Most of it affects architecture, so it is far cheaper designed in early than retrofitted during a deal. We work out which of it your target buyer actually asks for.
Yes, and it usually starts with knowing it, which many teams do not. Cost attribution per tenant, then the architecture that drives it — database design, background processing, storage tiers, and for AI features the inference spend. Gross margin is an engineering outcome as much as a pricing one.
Frequently. We start with a short audit of the codebase, the infrastructure and the release process, then agree what needs attention first. Taking over a product does not mean rewriting it, and the parts carrying most of the risk are usually fewer than they look.
Yes, and it is the arrangement we prefer. Your team holds the product context, we bring capacity or a specific capability, and both work to the same roadmap. What we avoid is a parallel team building in isolation, which produces integration debt nobody planned for.
.png)
Research report
Don't run your tech stack on unverified SaaS myths.
.png)
Research report
Close the gap between buying AI and adopting it.
.png)
Blog
A rising cloud bill usually isn't a pricing problem, it's an architecture one. This blog shows how a single number, unit cost, tells you which you're facing before the next invoice does.