What we do
Four areas. They tend to arrive together — an organization wanting AI in production usually discovers its data governance and its platform need attention first.
AI architecture and agentic automation
An AI roadmap tied to operations rather than to hype. We identify the manual bottlenecks worth automating, design the LLM and agent workflows to do it, and put them into production as repeatable pipelines.
- Where AI pays, and where it will not — assessed before you commit
- Agentic workflows for content publishing and operations
- Automated customer support and lead qualification
- Manual processes converted into pipelines that run unattended
Data governance and AI reliability
The half that decides whether an AI feature is trustworthy enough to leave running. Standards for evaluating prompts and outputs, data quality protocols, and clear rules about what proprietary data may be exposed to which model.
- Prompt and output evaluation standards
- Data quality protocols feeding AI workflows
- Controls that keep proprietary data contained
- Guardrails that keep hallucinations out of production output
Platform modernization and IT redesign
Legacy infrastructure into a cloud environment that scales, with the cybersecurity standards that should have come with it — and the organizational restructuring that makes the change hold after we leave.
- Legacy to cloud, planned in stages rather than as a rewrite
- Modern security standards and hardening
- Deployment automation, so releases stop being events
- IT organizational design — the roles the new platform needs
Capital efficiency and vendor optimization
Technology spend accumulates in layers, and nobody owns the total. We map what you pay for, find the overlap and the shelfware, and redirect the budget toward work that produces something.
- Third-party vendor stack review
- Overlapping tooling consolidated
- Internal workflows streamlined
- More engineering output per dollar spent
How we engage
Assessment
A short, paid piece of work that establishes what you actually have, what is in the way, and what is worth doing. It stands on its own — you are not committed to anything after it.
Advisory or fractional leadership
Ongoing senior involvement without a full-time hire. Setting direction, standards and priorities, and being available to the team doing the work.
Hands-on delivery
Where it is faster for us to build it than to specify it. Production code, infrastructure and automation, documented so your team can own it afterwards.