The plan before
the build.
Paid design and discovery. We connect to your systems, meet with stakeholders across each department, and deliver an architecture blueprint, per-department scope of work, and an AI readiness and governance framework. Fixed-fee phase that locks the scope of the engagement.
Digital Maturity Assessment
Your Firm vs. Benchmark
“Buying point solutions without a plan is how firms end up with fifteen tools and no infrastructure.”
AI readiness requires a data foundation, a clear architecture, and a sequenced plan. Not another subscription.
Assessment
Score Every System. Map Every Gap.
Current state vs. target state across your data, automation, and AI readiness. Each gap gets a severity rating and a build-or-buy recommendation.
- Full audit across data, pipelines, models, reporting, and AI infrastructure
- AI readiness scoring: which use cases are viable with your current data
- Every gap ranked by business impact and effort to close
System Scorecard
Current vs. Target Maturity
Recommendations
| System | Gap | Action |
|---|---|---|
| Data Layer | 3.5 | Buy |
| Underwriting | 2 | Build |
| Reporting | 3 | Build |
| Deal Intake | 4 | Build |
| AI Readiness | 4 | Build |
| Market Data | 2.5 | Buy |
AI Governance
Deploy AI You Can Defend to Your IC.
Agents that touch underwriting, reporting, or investor deliverables need guardrails. We build the governance layer that makes AI outputs auditable, traceable, and compliant with your firm's policies.
- Source attribution on every AI-generated assumption: traceable to page, table, and document
- Hallucination detection and flagging before outputs reach decision-makers
- Compliance frameworks for AI-assisted investment decisions and investor reporting
- Vendor evaluation: scored comparison of AI platforms, data providers, and automation tools
AI Governance Dashboard
Agent Oversight & Compliance
Always
Cited Outputs
Per policy
Logged
Flagged for Review
Audit trail
Required
Reviewer Sign-off
Pre-publish
Agent Output Validation
PassingEvery agent-generated underwriting assumption is traceable to a source document
Source Attribution Audit
PassingFull lineage from extracted value to page, paragraph, and table in the source OM
Hallucination Detection
2 FlaggedFlagged 2 assumptions with no source match in last 48 hours
Compliance Framework
ActiveAI-assisted outputs reviewed before IC submission per firm policy
All AI-assisted outputs require human review before investment committee submission
Roadmap
12 Months. Named Owners. Every Phase.
Data layer first, then automation, then AI agents. Each phase has budget ranges, build-or-buy scoring, and a named owner.
- Phased rollout: data layer, automation, AI agents, scale
- Build vs. buy scoring with vendor shortlists on every line item
- If you decide to build, we implement and operate it
Technology Roadmap
12-Month Plan
Workshops
Hands-On. Not Slide Decks.
Half-day sessions where your leadership team builds with AI agents and real portfolio data. You leave with a roadmap and assigned ownership.
- Executive AI literacy: what is real, what is noise, what matters for your firm
- Live builds with Claude agents, document extraction, and automated reporting
- Impact vs. effort prioritization scored with your leadership team
Executive Workshop
Half-Day Session
Current State Review
Map systems, workflows, and pain points across acquisitions, asset management, and reporting
Technology Landscape
Scored vendor comparison with build vs. buy on each gap
Prioritization
Impact vs. effort matrix scored live with your team
Roadmap + Assignments
Named owners, target dates, and budget ranges
You leave with a drafted roadmap and assigned ownership.
Ready to build your AI strategy?
One call to assess fit. A paid, fixed-fee discovery phase delivers the architecture blueprint, governance framework, and per-department SOWs that lock the scope of the engagement.