What does consultance.ai build?

Source-grounded AI deal desks and finance systems: diligence, reconciliation, financial close, reporting, underwriting, and compliance knowledge workflows — designed, deployed, and maintained end-to-end.

Who does consultance.ai work with?

Private equity funds, private credit teams, CFO offices, family offices, broker-dealers, and regulated finance teams that need faster, traceable workflows around confidential financial and deal data.

What makes a finance AI system trustworthy?

Material outputs need source links, verification states, approval controls, audit logging, and a clear exception path. The system automates the intelligence work while the finance or deal team retains judgment and final approval.

How long does an AI deal desk or finance automation build take?

A scoped proof of concept typically runs on representative data first. Production timing depends on data condition, integrations, deployment requirements, and the number of workflows in scope.

Do you transfer code and IP?

Yes. Code and IP transfer at every milestone. No subcontractors, no offshore handoffs — direct line to the engineers building.

Do clients own the system?

Yes. The engagement is designed around client-owned code, prompts, data, and deployment. The team can run the system independently or retain consultance.ai for support and further build work.

Services · Last updated Jun 2026

AI strategy that ends in a working build, not a deck.

Strategy is a sequence of decisions about what to build first, why it matters, and how success is measured. Use cases ranked by payback. Data requirements mapped. Architecture chosen. Timeline and budget on one page.

What we build

AI readiness review

Use-case portfolio

ROI and feasibility scoring

Architecture and vendor selection

90-day implementation roadmap

Why it matters

Strategy without code is a recommendation. We deliver both. The roadmap exists to feed the build queue, not to sit in a Drive folder.

Align leadership on what is worth building
Pick projects with real payback
Move into build mode immediately

Why most AI strategies never ship

MIT's 2025 enterprise study put the share of corporate GenAI pilots showing no measurable P&L impact at 95 percent. The pattern behind that number is consistent: a strategy authored by people who will never touch the build, handed to a team quoted against a spec that stopped matching reality the week it was written. The deliverable was a document, so a document is what shipped.

We structure the engagement so that failure mode cannot happen. The person who writes your roadmap is the person who writes the code in month two. Every use case on the list carries a build estimate we are personally on the hook for, which keeps the rankings honest. Nobody pads a roadmap they have to deliver.

What the roadmap actually contains

One page per use case: the workflow today, the workflow after, the number that moves, the data it needs, the systems it touches, the build estimate, and the risk controls. Then a stack-ranked sequence by payback period, a reference architecture for the first three builds, and a 90-day plan with named owners. No market-sizing chapter. No maturity matrix. Decisions.

You can pressure-test our approach before engaging: the strategy prompt packs in our free build library run the analyst layer of this process (market entry, competitor teardown, business case) inside your own Claude tenant, on your own data. If the free version earns your trust, the engagement is us doing the full job with you.

Questions about ai strategy consulting

What should an AI strategy include?

Goals, ranked use cases, data readiness, architecture, risk controls, owners, timeline, budget, and success metrics.

Can you build after the strategy?

Yes. The strategy feeds directly into pilot and production work.

Is this the same as AI transformation consulting?

Same destination, different unit of work. Transformation programs run top-down across the org chart. We run bottom-up: ship one workflow that moves a number, let the win fund the next one. Three shipped systems transform more than a transformation office.

How long does an AI strategy engagement take?

Two to three weeks to a decision-ready roadmap: ranked use cases, architecture, budget, and a 90-day build plan. It is short on purpose. The value is in what gets built next, not the document.

Who needs to be in the room?

Whoever owns the P&L the workflow touches, plus one person who actually does the work today. Strategy written without the operator in the room is how you get pilots nobody uses.

Try it free before you hire us

These free builds from our AI build library show exactly how we approach ai strategy consulting. Run one yourself this weekend — when you want it wired into your real stack, that is the engagement.

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