AI systems & internal tools
Available for consultingFor owners, operators, and lean teams replacing spreadsheet tracking, inbox triage, and verbal handoffs with dependable tools built around the way people really work.
Selected work
Each case study distinguishes shipped behavior from prototype scope, shows how the system moves data and decisions, and avoids invented customer or usage claims.
A browser-based collaboration flow that lets a host keep MIDI hardware local while a remote player sends expressive controls through a shared session.
Host-created sessions and remote joining are implemented in the public beta.
A private-knowledge operations prototype that turns a controlled document corpus into an evidence-oriented workspace for finding and reviewing answers.
The prototype exercises ingestion, retrieval, and evidence review with a synthetic corpus.
A governed operations console that turns a synthetic project portfolio into a visible intake, review, prioritization, and reporting workflow.
The reference implementation performs read-only fingerprinting, change classification, and bounded review queues.
Engagement formats
No vague transformation package and no unapproved public pricing. Each format names its fit, duration, ownership boundary, deliverables, and exclusions.
Compare engagement formatsA focused diagnosis of one costly workflow, the evidence behind it, and the safest route to a useful system.
Teams that know a workflow is costly but are not yet sure what to automate or build.
A bounded implementation sprint that turns a validated workflow into a working product slice—or gets a stalled build moving again.
Lean teams that need visible progress and one defined outcome without staffing a full product squad.
Ongoing technical ownership for teams that need a dependable partner to improve a system after its first release.
Teams with a live workflow or internal product that needs steady iteration, guardrails, and operational care.
How the work moves
The implementation stays tied to the actual workflow, the people responsible for it, and the evidence needed to decide what should ship next.
Start with the place work gets delayed, repeated, lost, or made difficult to inspect.
Map the people, decisions, data, constraints, and review points the system must respect.
Build one useful product slice, verify it against the workflow, and document what comes next.
Start with the messy part
Share the current workflow, who deals with it, where it breaks, and what a better system would make possible. That is enough for a useful first conversation.