01
Agents and workflow code
We build or refactor the agents and workflow plumbing when the sequencing identifies a consequential workflow worth shipping. The constraint is scope and measurement, not whether the system includes agents.
New, with Accorian: a real-time AI governance framework for control drift in enterprise AI.Read the framework
AI Transformation
AI Transformation
Move AI into the workflows that change the P&L. We build it into the priority work, attribute the revenue, margin, or cycle-time gain it creates, and leave the evidence trail that defends the change.
Spectrum3
Trust layerbuilt-in
Ownersnamed
Measured in production, not just shipped.
Every claim in the report traces back to source evidence, ownership, and the workflow decision it supports.
Valuefund next
Riskcontain now
Fluencytrain where work changed
What we build
Hands-on implementation, not a strategy slide.
Once the bets are sequenced, AI Transformation runs the rollout against them: build AI into the priority workflows, attribute the value it creates, and ship the operating playbook your team keeps using.
02
Evals and observability
Trace capture, eval pipelines, workflow metrics, and exception routing ship with the build. The instrumentation is how the workflow stays reliable after launch, not a bolt-on test rig.
Open03
Value and risk together
Each workflow ships with its business-outcome measure and the controls that defend the change, so the upside and the record run on the same evidence.
04
Method transfer
Fixed-scope deliverables, owners, runbooks, and measurement patterns transfer to your team, so the workflow keeps running and improving after we leave.
How the engagement runs
One shape, four phases.
An engagement shape, not a sector catalogue. The phases run the same whether the work lands in private equity, banking, fintech, asset and wealth, insurance, or real estate. Finance is where we go deepest, and the method ports to the rest.
Discovery
approved and shadow AIworkflow candidatesgovernance foundation
Vendor evaluation
build versus buyper-vendor scorecardsrollout order
Proof of concept
build the priority workflowvalidationeval baseline
Rollout
production launchtrainingboard-ready reporting
Operating playbook
ownersrunbooksmeasurement patterns
Value-Capture Report
investor-readypopulated by your team
Where AI pays, by sector
The highest-leverage workflows we build into.
The six segments where we operate. Each is a starting catalogue, not a closed list.
Private equity
Portfolio-wide value proof
One path to evaluate, build, and govern AI across portfolio companies, with reporting fit for executives, boards, sponsors, and supervisory review. The engagement produces the value proof and the board-ready trail behind it.
OpenBanks and capital markets
Deflection and developer AI
Chatbot deflection, customer-experience automation, and developer AI tooling, built into the workflows that move service cost and engineering throughput, with the controls examiners expect held on the same evidence.
OpenFintech
Vendor spend and customer AI
Rationalize AI vendor spend, then build the customer-facing AI that carries revenue, with the eval pipeline that lets a procurement reviewer sign without a rewrite.
OpenAsset and wealth
Research and advisor workflows
Research workflows, advisor productivity tooling, and client-facing AI, built against time-to-decision and analysis quality, with the trace lineage that survives review.
OpenInsurance
Claims and underwriting
Claims triage, underwriting copilots, and fraud indicators, built into the workflows that change loss ratio and cycle time, with disparate-impact testing and human review on every adverse action.
OpenReal estate
NOI-anchored operations
Leasing intelligence, CapEx prioritization, predictive maintenance, and valuation prediction, each framed against a per-property net-operating-income delta, with the data architecture that makes the delta measurable. Runs under NDA.
OpenWhat we have delivered
Real results, each carrying its real qualifier.
The same eval pipeline that gates whether a customer's AI earned its place also gates what we claim, which is why 95% stays stated and $20M stays modeled.
What this addresses
Deployed is not the same as working.
The four ways AI work stalls after it ships, and what the transformation pass does about each.
01
Pilots that never leave the lab
AI work stalls in side projects nobody can defend to a board. We focus the pass on a workflow that changes revenue, margin, or cycle time.
02
Shipped without proof
Most production AI lands in the record before anything shows it earned its place. Each workflow ships with the eval evidence that defends it.
03
No line to the P&L
Deployed, but no attribution. We tie the workflow to the revenue, margin, or cycle-time gain it creates, in a form a board can read.
04
Nothing that sticks
The vendor leaves and the workflow decays. Owners, runbooks, and measurement patterns transfer, so your team keeps it running.
Common questions
Common questions, direct answers.
Yes. The upstream sequencing includes prioritization, so we tell you which workflow to start with from the data, skip the broad vendor evaluation, and accelerate into proof of concept and rollout. The engagement compresses to a shorter, focused window.
Specialist AI builder, across the board
One builder, across the board.
We take your AI from strategy to outcome, with governance, audit, and evals built into every build. Start with a discovery call, or a quick audit.