The agent layer for
transaction services.

Agents that read the data room, build the analysis and draft the report. Your team reviews and signs.

The Jony desktop app showing an engagement workspace: data room index, EBITDA bridge and draft report sections side by side
Who it is for

A new way to run a diligence.

Agents change how the work gets done, not who does it. The same way of working holds whatever the size of the team.

An empty boardroom with a long table
BIG 4 DEAL TEAMS
Inside a large deal team

Agents carry the tie-outs, the chases and the exhibits, so every workstream arrives at review already evidenced.

An empty meeting room with a square table
INDEPENDENT ADVISORY
Inside a small advisory firm

The same scope, the same audit trail, the same standard of report, run end to end by the people who signed it.

The layers

What sits under a report.

Models at the bottom, your signature at the top. Each layer does one thing, and each one can be checked.

  1. 01

    Models

    Frontier models from Claude, OpenAI or Grok, on your own subscription. Swappable, never a lock-in.

  2. 02

    Harness

    Planning, tools and tests around each model call. One agent, one job, one output, checked before it lands.

  3. 03

    Your data

    The data room, the trial balance, the databook. It stays in your environment and never trains anything.

  4. 04

    Your method

    Your report template, your databook conventions, a few past reports. Encoded once, followed on every deal.

  5. 05

    The agents

    Families of agents: data room, earnings, balance sheet, report. Each one writes to your method.

  6. 06

    Your review

    Scope, open items, every number traced to its source cell. Judgement and sign-off stay with your team.

Demo

The databook is built before you open it.

One mandate, start to finish. You start at the judgement calls.

The app

The app is the easy part.

Set the scope, then work the list. It is built to the way your team already runs an engagement, on the model and the files you already have.

Scope

Name the entities, the periods and the workstreams once. Every agent works to that scope, so a tie-out in Germany and a peg in the UK land in the same engagement.

Open items

Every gap an agent finds becomes an item with an owner and a status. Client answers land against the item that raised them, and the completeness log updates itself.

TAILORED

Built to your method

Your report structure, your databook conventions, your order of priority. Nothing new for the team to learn.

ANY MODEL

Plug in the model you pay for

Claude, GPT, Grok, or a model on your own machine. Switch mid-engagement, nothing else changes.

Claude OpenAI Grok Cursor local model
YOUR FILES

No migration, no new file store

Workbooks, decks, documents and PDFs, read from your folders and written back in the same formats.

XLSXPPTXDOCXPDFCSV
Process

Four steps, in the order you already work.

You keep your method. The agents sit inside the process your team already runs and take the assembly work.

  1. 01 / INGEST

    Read the room

    Point an agent at the data room. It indexes every workbook, ties the trial balance to the databook, and lists what is missing.

  2. 02 / ANALYSE

    Build the analysis

    EBITDA bridge, normalised working capital, net debt and debt-like items. Each figure carries its source cell. Each adjustment carries its evidence.

  3. 03 / DRAFT

    Write the sections

    Sections come back in your template and your house voice. Findings are ranked by what moves price.

  4. 04 / COORDINATE

    Keep the client moving

    Open items become an information request list. Client answers land against the item that raised them, and the completeness log updates.

The agents

Dozens of agents, grouped into families.

A diligence report is a few hundred small jobs. Each agent does one of them: a tie-out, a peg, an exhibit, a chase email.

YOUR METHOD, ENCODED ONCE Mandate · Project Atlas 4 entities · FY22–FY24 · QoE, NWC and peg, net debt
01Data and completeness
  • data room indexerVDR export · 412 files index · 9 folders412 files, 3 duplicates58 s
  • file classifierindex file map398 classified, 14 unknown22 s
  • trial balance tie-outTB_FY22-24.xlsx · GL extract databook · tab 03411 lines tied, 1 exception41 s
  • databook builderTB · mapping databook_v4.xlsx6 tabs, 23 linked cells37 s
  • completeness logindex · scope gaps.md9 gaps open9 s
  • IRL managergaps · client replies IRL · 14 items6 answered, 8 chased12 s
412 FILES INDEXED · 9 GAPS OPEN

A databook that ties to the trial balance, and a written list of what is still missing.

One mandate fans out into families of agents. You describe the engagement the way you always have; the split into jobs is ours.

databook buildertrial balance tie-outadd-back adjudicatorEBITDA bridgecohort analysismargin walkrun-rate & annualisationrelated-party screenNWC normalisationseasonality & peg
debt-like classifierrestricted cash screencapex & lease reviewEBITDA to cashsection drafterfindings rankerexhibit buildercross-reference checkerIRL managermanagement call prep
Data handling

Client data does not leave your environment.

Diligence material is the most confidential data a firm handles. The product is built around that.

Beta firms get the data-handling note, the model setup and a walkthrough of what is logged, before any deal data is loaded.

COMMITMENTS06
  • Runs locally or in your own tenantnothing is uploaded to us
  • Bring your own model subscriptionno tokens resold, no quota caps
  • No client data used for trainingwritten into the contract
  • Every figure traces to a source celldatabook reference on every line
  • No output leaves without a reviewera person signs, not the model
  • Built by people who ran the worktransaction services, M&A, investment
Formal certification is on the roadmap, not claimed today.

Why we built it

From people who did due diligence, M&A and investment work for years.

We did this job for years. Building the databook took days. Reading it took a morning.

So we built agents to do the building. They follow your method, they never make up a number, and the person who signs still decides.

Jony · private beta
Questions

What partners ask first.

01

Does this replace the analyst?

No. It takes the reformatting, the tie-outs, the file chasing and the rebuilt schedules. Judgement, client calls and sign-off stay with the team.

02

Where does our client data go?

Into your environment and nowhere else. The agents run locally or in your own tenant, on your own model subscription. We do not hold deal data and we do not train on it.

03

How do we know a number is right?

You can open it. Every figure carries its source cell and every adjustment carries its document. Anything that rests on a judgement call is flagged.

04

How granular does it get?

Down to the artefact. There is no single diligence agent. There is a tie-out agent, a peg agent, an exhibit builder, a chase drafter. Each has one job, one output and its own tests.

05

Will it work with our report template?

Yes. We take your report structure, your databook conventions and a few past reports, and the drafting agents write to them.

06

What does the private beta involve?

One live engagement, run in parallel with your normal process, so you can compare the output. We take a few firms at a time and work with the team on the first deal.

07

What does it cost?

Nothing during the beta, and no commitment beyond an NDA. Pricing comes after, and you will see it before anyone asks you to pay.

08

What is it bad at?

Anything that needs a room. It will not read a management team, negotiate a peg or decide how hard to push an add-back. It also needs a real data room. Point it at forty scanned PDFs and it will tell you the room is incomplete.

Bring the agents to your next engagement.

Private beta, a few firms at a time. Free while it runs, and no client data needed to evaluate it.

Private beta · free during the beta · no client data required to evaluate