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AI for the work your team repeats.
Built in your tools. The code is yours.

We find the recurring workflow that costs your team the most hours in finance, operations or client service, and build it inside the tools you already use. Every number links back to its source, human review stays at each approval step, and you keep the code.

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Works with your tools
  • Excel
  • SharePoint
  • Slack
  • Notion
  • Salesforce
  • NetSuite

What the system does
for your team

Works where your team works

It reads from the spreadsheets, inboxes, client records and systems you already use. Nobody has to learn a new tool.

Produces the actual output

Reconciliations, reports, research and replies, drafted to your format and routed to the right person for review.

Answers from your own documents

Every answer points to the page it came from, and people only see sources they already have access to.

Agents built around your work
Connected to your tools.
Governed by your team.

Illustrative Consultance agent builder: a connected workflow, scoped tool permissions and a test run waiting for human approval

The process

How an engagement works

Each step ends with a decision, and you can stop after any of them. Start with one workflow, then add the next once the first is running.

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  1. A 30-minute audit call

    We map one recurring workflow with you: the tools involved, where the hours go and the review controls it needs. You leave with a written audit and no obligation to continue.

  2. A written scope

    If it is worth building, you get the scope in writing: the workflow, the sources it connects, the controls and the price.

  3. Proof on your data

    We run a scoped proof of concept on representative data first, so you see real output before anyone commits to a production build.

  4. Built in your environment

    The system runs in your cloud tenancy or on your own machines. Access, approved model providers, retention and review steps are agreed before work starts.

  5. Handed over to your team

    You receive the code, the prompts and the operating documentation. Ongoing maintenance and accuracy checks are scoped with you.

Systems we build

consultance.ai systemWorkflowsFrom incoming records to an owned next step
Run intake, analysis and reporting as one controlled sequence. Your team reviews the output with the sources and assumptions alongside it.

Who we build for

Your environment.
Your controls.

Private deployment, source visibility, and human review at the points where judgement matters.

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Private deployment

Built around your data boundary.

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Evidence & review

Sources beside the decision. People at the approval point.

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Ownership

Your workflow, knowledge and code stay yours.

From the work

Diligence moved from months to weeks. The numbers stayed connected to the evidence, and the system stayed inside the fund's environment.

Private equity diligence Anonymized Consultance case study

Notes from the work.

All insights

A few practical answers

Before we build.

What does consultance.ai build?

Consultance provides AI consulting and implementation for finance and operations teams. We build source-grounded deal desks, reconciliation, financial close, reporting, and private knowledge systems around your existing tools and review process.

Who does Consultance work with?

Investment banks, private equity and private credit funds, CFO teams, family offices, real estate firms, property managers, and professional-services teams with recurring document, knowledge, or operational work.

How is a custom system different from a standalone AI tool?

The system connects your sources, permissions, integrations, and approval steps to a defined workflow. Your team receives the code, prompts, and operating documentation, with maintenance and accuracy support scoped alongside the production build.

How do you handle confidential data?

Deployment is scoped around your data boundary, whether that is your cloud tenancy or a local environment. Access permissions, approved model providers, retention, and review controls are agreed before implementation. Confidential documents are not required for the initial audit call.

How are AI-generated outputs reviewed?

Material figures and claims stay linked to their source evidence. Verification and exception handling identify what needs attention, and your team retains responsibility for judgment and final approval before an output enters a decision or operating process.

Where does an implementation start?

A founder-led audit maps one recurring workflow, its cost, and the controls it needs. A scoped proof of concept tests representative data before a production build. Timing depends on data condition, integrations, and deployment requirements.

Newsletter

Notes from the work

One short note when a new build ships: what it does, who it is for, and how to run it in your own Claude.

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Bring one workflow to a 30-minute audit.

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