LogiCov

LogiCov, Inc.

Institutional credit analysis without giving away the book.

Turns a 2-3 week credit file into a 2-3 hour desktop underwrite. Ingestion and synthesis, in your tenant, on your policy. One client's files, rule book, and memo language never touch another client's. Your data is never used to train anyone else's model.

Cycle time

2-3 weeks → 2-3 hours

See a desktop underwrite

The gap

Why the obvious tools do not work

Rated-public tools

Strong on rated publics. Weak on unrated publics and NDA privates, which is where most of the book actually sits.

Public AI / generic GenAI

Uploading NDA financials into a public model is a compliance event, not a productivity win.

We will build it with you vendors

The client funds the work. The vendor keeps the method and sells it to the next institution.

Institutions want AI and legally cannot use the obvious tools.

Ownership

Your memo. Your policy. Your tenant.

Your Data

Files stay in your tenant. Nothing is pooled across clients.

Your IP

Your policy, template, and memo language remain yours.

Your Environment

Single-tenant by design. No shared workspace.

Your Memory

Prior files and decisions compound inside your environment.

Memory stays with you. Processing does not leave a copy behind.

Containment

Same task. Two very different paths.

Containment, not a smarter model.

Drop it in a model

One prompt carries the file, the policy, the industry question, and the memo ask. The file leaves the workflow boundary. The model can answer outside the question. There is no separate check before the draft exists.

One window. No harness. No owner.

Narrow agents, one tenant

The file stays inside the institution's environment. A financial agent only spreads. An industry agent only reads the sector. A policy agent only checks their rule book. A guardian agent reviews before a human signs. Nothing is pooled. The analyst still submits to committee.

Each agent does one job. The institution owns the conclusion.

A general model is built for every question. This is built for one file: their policy, their template, their tenant. The draft does not wander into a chat.

LogiCov harness

  1. File in

  2. Narrow agents

    Spread, sector, policy

  3. Guardian check

    Kill switch. A reviewer can stop the draft before it exists. Nothing leaves the tenant.

  4. Human sign-off

  5. Committee

Ingestion and synthesis. The institution owns the credit conclusion.

Fit with the program

A desk win the transformation office can absorb

The enterprise AI program

  • Multi-year, multi-use-case.
  • Owned by IT.
  • Slow to reach credit.
  • Files still cannot go into public tools while it is being built.

What the credit desk needs

  • One workflow this month.
  • Policy-aligned desktop underwrites on publics, unrated publics, and NDA privates.
  • Isolated tenant.
  • No dependency on the platform program.

LogiCov is not a rival to the transformation program. It is a contained production use case the credit team can run now and the transformation office can adopt later. It does not wait on the enterprise platform and it does not interfere with it.

Outcomes

What changes when the file is measured in hours

2-3 weeks to 2-3 hours

Cycle time on a desktop underwrite.

Capacity

Analyst throughput without linear headcount.

Consistency

The same policy checks run on every file.

Institutional intelligence

Prior files and decisions stay in their tenant and route the specialist check to the desk that has seen that credit before. A trade-finance office and an ag office do not see each other's book. Audit can still find the odd file, because the pattern lives in the same institution. Construction default patterns and luxury-homebuilder default patterns stay on their book. Agents get better on their files. Nothing is pooled across clients.

95% final-ready

Source-cited draft, ready for human review.

No leakage

NDA files never enter a public model.

2-4 weeks

Live in a pilot, not a program.

A regional-bank analyst, fully loaded, is about $300-350k. Ten analysts is $3.5-4 million before a file is improved. Intake to a source-cited draft in hours, not two to three weeks.

Scale deal flow without scaling headcount.

Workflow

How the work runs

  1. 01

    Upload financials

    PDFs, Excel, data-room drop. Messy files are fine.

  2. 02

    Entity confirm

    Legal name, ticker, corporate tree. The file is attached to the right obligor.

  3. 03

    Agent review

    Spread, policy checks, discrepancy flags, source citations.

  4. 04

    Desktop underwrite

    Committee-format draft. 95% final-ready for the analyst.

We do not redesign the credit culture. We remove the grunt work in front of it. The analyst still owns the call.

Product simulation

A desktop underwrite, start to draft

Sample output. Public company. Generic Codex. Occidental Petroleum (NYSE: OXY). Full files are shown live on a name from your book.

logicov · tenant: sample · credit memo
Sample output

Generating desktop underwrite

Occidental Petroleum Corporation

  1. Ticker / legal name OXY confirmed
  2. 10-K / 10-Q ingested
  3. Spreading agent running
  4. Policy / rating agent running
  5. Reviewer agent checking consistency
  6. Draft ready · 95% final-ready for human review

Who runs it

Same product, different job

Commercial Banks

A committee-ready first pass in hours, inside the bank's own policy.

View

Private Credit

Screening memos that sound like your team, ready the same day.

View

Corporate Treasury & Credit

Limit files that hold up in review without a two week wait.

View

Trading Houses

Counterparty coverage that keeps pace with the trading book.

View

Insurers

Policy-locked files with the evidence attached.

View

Family Offices

Institutional output without institutional headcount.

View

Specialty Lending

A credible first look before the deal team commits weeks.

View

Advisory

Faster client turnarounds with your method kept in-house.

View

Adjacent outcomes

After the memo exists in the tenant, teams naturally get a shared workspace, prior-file memory, and a cleaner book.

These are outcomes of using the platform. They are not separate modules to buy.

Built from the chair

Kristopher Sherman, CEO

Kristopher Sherman, CEO. 20+ years in institutional credit and commodity risk, including as a director of risk on a major-bank commodity desk. LogiCov was built from the chair because the file was always the bottleneck, not the judgment.

Insights

Notes from the desk

All insights

Note 01

Credit teams are not short on judgment. They are buried in glorified data-janitor work.