Built to run at scale, from the first commit
A tool that works for one team is not a platform. The difference is multi-tenancy, identity, metering, quotas, observability, upgrade paths and an on-call story. Retrofitting those into a prototype is far more expensive than designing for them deliberately.
- 99.9%+
- availability target with a defined error budget
- N tenants
- on one codebase instead of N forks
- < 15 min
- mean time to detect against the SLO
- Per-unit
- cost attribution across business units
What it looks like today
The pattern we find in almost every operation
- A useful internal script becomes business-critical with no monitoring, no owner and no rollback.
- Each business unit forks the same tool, so you maintain six divergent copies.
- Your product roadmap is blocked on architecture decisions made for a demo.
- Partner or customer access needs tenant isolation that was never designed in.
- Usage cannot be metered, so the capability cannot be billed or cost-attributed.
- Nobody knows the system is degraded until a user complains.
How we do it
The approach, step by step
- 01
Decide the operating model first
Who runs it, who is on call, what the SLA is, how it gets upgraded, and what happens at 3am. These answers determine the architecture far more than the feature list does.
- 02
Design the tenancy and identity model
Single or multi-tenant, isolation boundaries, data residency, and how identity flows from your provider into every service. This is the decision that is genuinely expensive to reverse.
- 03
Build the platform substrate
API layer with versioning, background job processing, eventing, secrets management, configuration as code, and CI/CD with progressive delivery rather than a Friday-night deploy.
- 04
Instrument everything
Structured logging, distributed tracing, metrics with alerting thresholds tied to the SLA, and dashboards that answer 'is it healthy' without reading logs.
- 05
Meter and attribute
Usage metering per tenant and per business unit, so the platform can be charged back, budgeted and capacity-planned instead of being an invisible shared cost.
What you receive
Deliverables, stated up front
- Architecture decision records covering tenancy, identity, data and deployment
- Platform services: API gateway, job orchestration, eventing, secrets, config
- Multi-tenant data model with isolation and residency controls
- CI/CD with automated tests, environment promotion and progressive rollout
- Observability stack: logs, traces, metrics, SLOs and alert routing
- Usage metering and chargeback reporting per tenant
- Security review, threat model and dependency scanning in the pipeline
- Load and failure testing against the agreed performance envelope
You are a fit if
- More than one business unit or an external partner needs the capability
- The automation is on a path to being sold, bundled or resold
- You need per-unit cost attribution or usage-based billing
- The pilot works but has no observability, no rollback and no on-call owner
- Teams are already forking the same internal tool
We will tell you it is a fit problem if
- One team, one workflow, no external consumers — the platform overhead is not yet earned
- There is no operating owner and no appetite to staff one
- The product direction is still genuinely undecided
Systems we work with
Not on the list? We integrate against anything with an API, a database, a file interface or a documented import format.
Questions we get on this
Platform builds: the practical answers
Can you evolve an existing pilot into a platform?
Do we have to run it in our own cloud?
How do you handle compliance requirements?
Bring us the process you already know is costing too much
Thirty minutes with an engineer is usually enough to tell whether it is worth automating, roughly what it would save, and whether the payback is inside a window your finance team will accept. If the answer is no, we will say so on the call.