01
Scope
Choose one workflow worth changing.
Name the owner, the measurable baseline, the systems involved, and the decision that remains human.
GOVERNED AI FOR REGULATED WORK
Put one consequential AI workflow into production—without losing control.
Alpha Data Capital turns a promising AI use case into a bounded system with explicit authority, measurable tests, and reviewable evidence.
15 business daysto a decision-ready blueprint*
One workflowkeeps scope and ownership clear
Your stackvendor-neutral architecture
*After kickoff, required access, and stakeholder availability.
POLICY CHECK
REVIEWVendor exception request
Data boundaryApproved sources only
Agent authorityRecommend, never approve
Sensitive classesPII · account · legal
Required reviewerRisk operations
Trace ADC-0178 sealed with 12 evidence events
Human authority preserved
Release gate: controlled
Designed for consequential workflows across
FINANCE HEALTHCARE INSURANCE REGULATED OPERATIONS
01 The decision before the model.
WHY PILOTS STALL
The prototype is rarely the hard part.
The hard part is deciding what the system may see, what it may do, who can approve an exception, and what evidence proves it behaved as intended.
01
Value is vague. The use case has enthusiasm, but no baseline or accountable owner.
02
Authority is implicit. Model behavior gets discussed before tools, permissions, and human gates.
03
Proof arrives late. Security and compliance see screenshots when they need traces, tests, and operating controls.
THE CONTROLLED PATH
Every production decision earns its way forward.
The work is sequenced so business value, system access, risk, and proof become one delivery plan—not four disconnected workstreams.
02
Govern
Turn policy into executable boundaries.
Define allowed tools, sensitive-data classes, approval gates, refusal behavior, and escalation routes before the agent acts.
03
Prove
Test the failures, not only the happy path.
Run representative, edge, and adversarial scenarios. Capture the inputs, decisions, approvals, and outputs for review.
04
Launch
Ship with ownership and evidence intact.
Release behind a controlled boundary with monitoring, a runbook, rollback criteria, and a named operator.
THE FIRST ENGAGEMENT
Leave day 15 knowing whether—and how—to build.
Use-case scorecard
Impact, feasibility, risk, readiness, and a clear go / reshape / stop recommendation.
System boundary map
People, data, models, tools, integrations, permissions, and human decision points.
Control register
Sensitive-data classes, allowed actions, approval gates, exceptions, and owners.
Evaluation plan
Representative and adversarial scenarios, acceptance thresholds, and evidence capture.
Production roadmap
Sequenced build plan, dependencies, resourcing assumptions, and release gates.
Executive readout
A decision-ready briefing that aligns the sponsor, operator, security, and compliance teams.
The scope guardrail
The clock starts when the workflow owner, required system access, and subject-matter experts are available. New workflows, inaccessible systems, and production implementation become an explicit follow-on scope—not silent timeline drift.
REAL-WORLD CONTROL PATTERNS
Specific enough to evaluate. Honest enough to trust.
These are deployment patterns, not client-result claims. Each shows where AI can help and where human authority stays intact.
FinanceDEPLOYMENT PATTERN · NOT A CLIENT RESULT
Exception triage without autonomous approval
An agent assembles the relevant policy, transaction context, and missing evidence; a designated reviewer remains the approval authority.
- Read-only source access
- PII class handling
- Reviewer sign-off
- Trace for every recommendation
HealthcareDEPLOYMENT PATTERN · NOT A CLIENT RESULT
Referral intake with PHI-aware routing
An agent classifies documents, checks required fields, and routes the packet while clinical judgment stays with licensed staff.
- PHI and identifier classes
- Minimum-necessary access
- Source citations
- Clinical escalation path
InsuranceDEPLOYMENT PATTERN · NOT A CLIENT RESULT
Claims evidence assembly with bounded actions
An agent gathers policy context and supporting documents, flags contradictions, and prepares a review packet without deciding coverage.
- Role-scoped tools
- Protected-class testing
- Contradiction flags
- Human coverage decision
HOW THE RELATIONSHIP GROWS
Earn the next commitment with evidence from the last.
No giant transformation promise on day one. Start with a decision, build one bounded workflow, then expand only when the operating evidence supports it.
START HERE
AI Deployment Blueprint
Decide if one workflow is valuable, feasible, governable, and ready to build.
- 15 business days*
- Six concrete deliverables
- Written follow-on scope
BUILD
Controlled Pilot
Implement the approved boundary, evaluation suite, human gates, and evidence trail.
- Quoted from the blueprint
- Release gates agreed up front
- Team enablement included
OPERATE
Assurance & Expansion
Monitor behavior, review exceptions, retrace evidence, and qualify the next workflow.
- Performance and drift review
- Control and evidence checks
- Expansion by proof, not pressure
*Timing assumes kickoff prerequisites are complete. Pricing is provided after the fit review because data access and integration scope materially change the work.
STRAIGHT ANSWERS
What buyers usually need to know before the first call.
Still evaluating? Send the workflow, current stage, and success measure through the guided intake. We will tell you whether the Blueprint is the right next step.
Is this a software license or consulting engagement?+
The Blueprint is a fixed-scope professional engagement. A pilot can use your approved cloud and model stack; any recurring platform, support, or seat cost is stated separately in the written scope.
What counts as one workflow?+
One named business process with one accountable owner, a defined trigger and outcome, a bounded set of systems, and a shared success measure. Additional processes are scored separately.
How do you handle sensitive data beyond SSNs?+
We classify the data relevant to the workflow—such as account identifiers, health information, diagnoses, claim details, credentials, contracts, and internal business data—then define minimum-necessary access and handling controls for each class.
Does day 15 mean production launch?+
No. Day 15 is the decision-ready deployment blueprint. Production timing depends on integrations, controls, evaluation thresholds, and organizational readiness. The point is to expose those facts before a build budget is committed.
What makes this different from an AI strategy deck?+
The output is implementation-ready: a system boundary, controls, tests, dependencies, release gates, and owners. It should let a sponsor make a build decision and let a delivery team begin without re-discovering the fundamentals.
YOUR FIRST CONTROLLED MOVE
Bring one workflow. Leave with the path to a defensible decision.
The guided intake takes about three minutes. No blank email, no vague discovery call, and no assumption that every idea deserves a build.
Start the workflow fit check