Change the economics of advisory delivery

  • Up to half the cost to deliver the work
  • Your method stays yours. Client data is processed where it already sits
  • Every finding is traceable. Each one cites the document it rests on

Designed by people who know the work from every side

Valerii Vashchenko

Valerii Vashchenko

Ex-lead of a bank AI team:

Decisioning and recommendation systems, analytics, risk scoring.

Andrei Mitrofanov

Andrei Mitrofanov

Ex-KPMG Partner:

Deal Advisory, Head of restructuring practice.

Personally signed
1500+ reports.

Yan Serebryakov

Yan Serebryakov

Ex-executive banker:

Debt workout and restructuring.

Commissioned
180+ reports.

More about founders Learn our products Data security
The DD Toolkit inside PowerPoint, tracing a corrected trial balance: three source changes recomputed through eight databook figures and nine report pages, with the superseded values struck through.

The pressures
we see in advisory

Advisory still depends on a model built around people, hours and review. The pressure on each of those is increasing.

  1. 01

    Fixed teams meet an uneven pipeline

    People are the largest cost of delivery. Firms carry capacity between engagements, then compete for the same people when demand peaks.

  2. 02

    The team on the next engagement is never quite the same

    Junior turnover is high, experience varies, and knowledge leaves with people. Yet the standard of the work cannot depend on who happens to be available.

  3. 03

    Too much senior time goes into review

    Partners and directors still spend hours checking numbers, tracing evidence and correcting inconsistencies. Every hour spent reviewing avoidable errors is an hour not spent with clients.

  4. 04

    The tools have barely changed. The work has.

    Advisory still runs largely on Excel, Word and PowerPoint. New technology has to fit that workflow rather than force teams to relearn how they work.

  5. 05

    General-purpose AI is not advisory infrastructure

    Specialist work needs the firm's methodology, controlled access to client data, repeatable workflows and outputs that can be traced back to evidence.

Why we built Interiu

The technology came after the work

Between us, we have delivered advisory engagements, commissioned them, reviewed the reports, and built technology for regulated financial institutions. That gave us a different starting point: not what AI can do, but what advisory work actually requires.

Andrei Mitrofanov
We created the company we wished we had on the other side of the table.
Andrei Mitrofanov Former KPMG Partner
  1. 01

    Building this properly takes sustained investment

    Advisory firms are built to advise clients, not to fund specialist technology teams through years of development. Their capital earns its return doing what they do best: advising clients.

  2. 02

    General-purpose platforms solve a different problem

    Deal Advisory is not one use case: due diligence, valuation, restructuring and transactions each have their own methods, workflows and standards of evidence.

  3. 03

    Interiu makes the investment in technology, while advisory firms keep ownership of their methods, client data and judgement

    Your methodology stays yours. Client data is processed where it already sits. Every output is traceable.

Let's discuss where the hours go

Show us an advisory workflow that takes too much time, senior attention or manual work. We will tell you where we think technology can change it, and where it cannot.

Discuss your case