Client workFour engagements,
Four engagements,
told with the numbers attached.
Client names are withheld under NDA, so each record leads with the sector and the shape of the problem instead. Every one states what was true before, what we changed, and what moved as a result.
- 15×
- Deploy frequency
- −65%
- Forecast error
- −97%
- Audit prep
- −86%
- Time to interactive
01 — DevOps / SRELogistics · 2,400 staff
Releases went from a quarterly event to a Tuesday afternoon
- Situation
- Four business units shared one release train. A single failing change delayed every other team by a quarter, so nobody shipped anything small.
- What we did
- Split the monolith's delivery path per service, built one templated pipeline with automated rollback, and put error budgets in front of the leadership team every month.
- Result
- Deployments stopped being a negotiation. The same teams now release on demand, and incident length fell faster than incident count — which is the honest signal that recovery improved.
- Deploys per month
- 3 → 47
- Mean time to restore
- 9h → 22m
- Change failure rate
- 38% → 4%
02 — Data engineering & analyticsIndustrial distribution · $480M revenue
The Monday forecast stopped being an argument
- Situation
- Three teams produced three different revenue numbers from the same source systems. Half of every commercial meeting was spent reconciling spreadsheets rather than deciding anything.
- What we did
- Built one governed semantic model over the ERP and CRM, retired 40 hand-maintained reports, and put a single approved forecast in the meeting where the decision actually happens.
- Result
- Forecast error fell inside 10% within two quarters, and the reporting effort that used to consume a full-time analyst went away entirely.
- Forecast error
- 23% → 8%
- Manual reporting hours / month
- −140
- Use-cases live in year one
- 6
03 — Cloud & M365 · CybersecurityInsurance · regulated, multi-country
An audit that used to take six weeks now takes an afternoon
- Situation
- Azure and Microsoft 365 had grown organically across three acquisitions. Nobody could say who had access to what, and every audit became a manual evidence hunt.
- What we did
- Rebuilt the tenant on a governed landing zone with conditional access and privileged identity management, then moved control evidence into the pipeline so it is produced continuously rather than assembled on request.
- Result
- Access reviews are now generated, not compiled. The security team spends its time on threat work instead of screenshots, and cloud spend dropped as orphaned resources surfaced.
- Audit evidence prep
- 6 weeks → 1 day
- Standing admin accounts
- 34 → 0
- Cloud run cost
- −27%
04 — Web development · CXSpecialist retail · direct-to-consumer
A rebuild that paid for itself before the next season
- Situation
- The storefront took eleven seconds to become interactive on a mid-range phone, and the marketing team needed a developer to change a banner.
- What we did
- Rebuilt on Next.js with per-route rendering strategies and a headless CMS designed around how the team actually writes, then instrumented the funnel properly for the first time.
- Result
- Mobile conversion moved because the site got fast, not because of a redesign. Content changes that used to take a sprint now take ten minutes and no engineering ticket.
- Time to interactive
- 11.2s → 1.6s
- Mobile conversion
- +34%
- Content changes per week
- 2 → 30+
Want the version with the client's name on it?
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