Most institutions have plugged generic AI tools into consequential workflows and are hoping the output holds. We take a different approach. We build purpose-built AI systems around your most critical processes, deploy them inside your infrastructure, and hand them over permanently.
Built around your workflows, not a generic tool configured with prompts.
Deployed inside your infrastructure. Your data never leaves your environment.
You own it outright. Not a subscription. A capability your organisation keeps.
Every output is traceable to source. Built to satisfy institutional audit requirements.
The workflows below are where we are building first. These are workflows where AI currently falls shortest and where the cost of a missed signal is most consequential. This is not the limit of where the architecture applies.
Adversarial review, programmed to find reasons to fail the deal first, across 100% of the data room. Every contradiction surfaced before any investment case is built.
See the use case →Portfolio company performance tracked against the investment thesis. Leading-indicator alerts for EBITDA variance, covenant drift and credit stress before the reporting cycle, across the full portfolio, not just flagged positions.
See the use case →Structured credit analysis with full audit trail. Built to your credit committee format. Traceable from source to every conclusion.
See the use case →Beneficial ownership traced through complex corporate structures across jurisdictions. Inconsistencies in disclosed structures surfaced automatically, with a full audit trail built to compliance requirements.
See the use case →Together, they described a year of full cost exposure with zero revenue.
LP DDQs now routinely ask whether AI-assisted analysis can be audited, explained, and independently verified. This is not a future requirement. It is being asked on live mandates now.
"We use an off-the-shelf AI tool."
"We run 500+ verification checks against every data room, with a full cell-level audit trail built to IC review requirements."
If your current AI output isn't holding up to institutional scrutiny, we should talk.
Request a Private BriefingWe do not configure off-the-shelf AI tools. We build purpose-built AI systems from the ground up, designed around the specific demands of each workflow, deployed inside your infrastructure, and handed over permanently.
The workflows that matter most in financial services each present a distinct intelligence challenge. We engineer for all three.
Adversarial means the system is programmed to find reasons to fail the deal first, before any investment case is built. Every contradiction is surfaced and must be accounted for or disclosed. No conclusion is drawn from unverified inputs.
Ingest across entities, instruments, and time. Surface what each source reveals about the others. Continuous, not periodic. Designed for workflows that cannot wait for the next reporting cycle.
Build the document your committee expects, structured to your output conventions, with a full audit trail from source to every conclusion. Nothing asserted without traceable derivation.
Every finding in a Refoveo output is traceable to the exact source document, page, and cell it was derived from. Your team can navigate from any conclusion to the primary source directly.
This is not a summary with footnotes. It is a navigable decision chain built to satisfy institutional audit requirements, allowing your committee to interrogate every finding independently.
If a finding cannot be traced, it does not appear.
Every engagement follows the same three phases, designed to demonstrate value on your real data before any commitment, then build the right system around how your organisation actually works.
We run the full methodology against two of your closed deals. Your team sees exactly what it surfaces before any commitment is made.
A specialist embeds with your team. The intelligence system is calibrated to your workflows, your output formats, and how your organisation actually makes decisions.
Deployed inside your infrastructure, operated by your team, owned outright. You own the capability permanently, while we keep the underlying AI current as the technology advances, so every improvement is a free upgrade to what you own.
Refoveo is deployed inside your Virtual Private Cloud. Your data, your workflow logic, and your proprietary calibration never touch a public network at any stage of the engagement.
| VPC Deployment | Runs inside your infrastructure. Not a shared cloud. |
| Zero Retention | Nothing stored or processed outside your VPC boundary. |
| No Model Training | Your data does not train any public model. Ever. |
| Regulatory Alignment | Designed against FCA and SEC AI governance frameworks. |
| Full Audit Trail | Cell-level decision chain built for institutional compliance review. |
We are starting in institutional finance, where the stakes are highest, the data is most complex, and the cost of a missed signal is most consequential. These are the first three use cases.
The greatest risks in a data room are not in any single document. They are in the contradictions between documents. A construction schedule and a revenue model. A management account and a disclosure letter. Standard review processes are not designed to catch what is mutually contradictory across hundreds of files.
We run an adversarial pass across 100% of the data room before any synthesis begins. Every contradiction is surfaced and must be accounted for. The IC first draft is generated in the same session, structured to your format, traceable to source.
A 9-month gap between construction completion and revenue commencement: invisible to standard review, visible to adversarial analysis. Confirmed before capital was committed.
Quarterly reports tell you what happened. By the time covenant drift or credit stress appears in a report, the window to act has often closed. You need to know what is developing, across the full portfolio, not just the positions your team has flagged.
We build continuous surveillance across your portfolio, ingesting management accounts, covenant schedules, and operational data as they arrive, surfacing leading indicators before they become problems.
Credit decisions require structured analysis that a credit committee can interrogate and a regulator can audit. Generic AI tools produce confident-sounding summaries that cannot be traced to source, creating institutional risk rather than reducing it.
We build credit analysis systems calibrated to your underwriting standards, structured to your credit committee format, with every assertion traceable to the underlying data.
Supplier financing structured as trade payables. Related-party transactions arranged to avoid balance sheet recognition. Inconsistencies between facilities disclosed to lenders and those disclosed to auditors. The mechanisms were visible to an engine designed to look for them.
KYC reviews require tracing beneficial ownership through complex corporate structures, spanning jurisdictions, entities, and document types that do not always tell the same story. Standard processes rely on analysts manually cross-referencing documents that were never designed to be compared against one another.
We apply the same adversarial cross-document methodology to ownership and compliance review, surfacing inconsistencies in disclosed structures, flagging documents that contradict each other, and producing a fully traceable output built to satisfy compliance requirements.
These are the workflows where we are building first, not the boundaries of what we can build. If your workflow is not listed, that is the conversation we want to have.
We are building Refoveo because we know what institutional financial workflows actually demand. We have seen, first-hand, what happens when the analysis misses what matters.
14+ years in institutional finance, capital markets and private markets. The methodology is built directly from that experience.
Risk and change executive with over 30 years of leadership experience in investment and international banks. NED, board advisor, and active investor.
Every figure we publish is sourced to the actual data it came from. The real finding is more compelling than an inflated one, because it is true and verifiable.
Your data stays inside your environment at every stage. No public network exposure. No shared model training. No exceptions.
Every engagement is designed to build permanent capability inside your organisation. We are explicit about what we commit to, and we hand it over.
We review every submission personally. Response within one business day. All submissions treated as confidential.
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