Six practices, delivered hands-on in energy, utilities, healthcare, financial services and SaaS. Each one lists what you get and where the work usually starts.
When analysts rebuild the same extract by hand every month, the problem is rarely the report. We design analytical data stores, migrate legacy operational stores, and put an abstraction layer between reporting and the source schema so a schema change stops breaking dashboards.
A two-week assessment of the current stores, the reports depending on them, and the changes that keep breaking. You get the findings whether or not you continue.
See a utility data platform engagementAccess models fail in one of two directions: too open to pass an audit, or so restrictive that people work around them. We design RBAC schemas and row-level security against the Active Directory groups you already maintain, and we apply confidentiality, integrity and availability as design constraints rather than a checklist at the end.
Tightening access surfaces the accounts that were quietly over-privileged. Expect a short window of access requests after cutover, and plan someone to own them.
A suite nobody trusts costs more than no suite at all, because someone still spends their week triaging false failures. We build end-to-end frameworks on SerenityJS using the screenplay pattern, wired into Jenkins for nightly runs with alerting and reporting a product owner can act on.
A proof of concept on your highest-risk flow, reviewable before you commit to the full framework. One recent build reached 400+ automated tests in four months.
See the QA rebuild engagementWe build AWS-native services on Lambda, Bedrock and OpenSearch Serverless, defined in CloudFormation and released through the same pipeline as the rest of your platform. AI features are scoped against a measurable retrieval or accuracy target, not a demo. AWS AI Practitioner certified.
Managed AI services move fast, and a model or endpoint you depend on can change under you. We pin versions and name the review interval in the handoff.
Modernization goes wrong when it becomes a rewrite nobody scheduled. We assess what you have, sequence the work so operations keep running, and automate the manual steps that cost your team the most hours. One onboarding automation cut customer setup time by 90%.
A legacy assessment scoped to one system and the processes around it, ending in a roadmap you can fund in stages.
See the onboarding automation engagementPrograms stall in the gap between what leadership decided and what engineering understood. We run weekly executive sessions and cross-functional roadmap work, and we translate in both directions — including when the honest answer is that a date will not hold.
We work inside your framework, whether that is SAFe, Scrum or no framework at all. We have delivered in weekly sprint cycles reporting to a CEO and in exploratory work with no ceremony.
Who you work withA founder reads every message. We reply within two business days, and we will tell you if this is not work we should take.
