DataBridge in two pages, for your reviewers

What it is, the problem it answers, how it works, where it runs, how it was tested, how a pilot runs and who we are. Print it or forward the link.

For your IT and security reviewers, the Technical overview has the detail.

What it is

DataBridge by Walnut connects the information spread across your existing systems into one record your teams can use. Ask a question in plain English and get the answer from your data, with the source on every figure. It runs on your own machines, and nothing leaves your control.

The problem it answers

25% of a team's time goes to searching for answers. Atlassian, State of Teams 2025, 12,000 knowledge workers.
5.3 hours a week, per person, spent waiting on colleagues for information or recreating work that already exists. Panopto with YouGov, 2018, 1,001 employees.
42% of an organisation's know-how is held only by individual employees. When they move on, it goes with them. Panopto with YouGov, 2018, 1,001 employees.

Two layers on one foundation

A Company Brain that connects your data, and the intelligence layer your teams use to ask questions, get reports and draft routine work.

How it works

Five steps take your data from the systems it sits in to a record your teams can check.

Connect

Reads databases, documents, spreadsheets, email and the systems your teams use.

Understand

Recognises the same customer, supplier, project or person across every source and links them into one record.

Convert

Gives each job the information in the form it needs: answers, reports, tables for analysis, and data ready for AI tools.

Prove

Each figure read from a file points to the cell, line or page it came from, and shows whether it has been checked.

Protect

Runs on your machines, with the AI model you choose. Each person sees only what their role allows.

Where it runs, and who sees what

Your choice of model: use the AI model you prefer, run it on your own machines, or use none. Matching records, reconciling figures, reports and exports work without any AI.
Runs on your machines: installed on hardware you control. When it is installed on your own premises, nothing is uploaded and nothing connects out.
Access by role: each person sees only what their role allows. Confidential material is kept separately, locked with its own key.
A person confirms what AI proposes: facts a model suggests wait for a person to confirm them, and drafted emails go out only after approval.
Every version is kept: corrections add a new version and keep the old one, so you can see what the record said on any past date.
Leave with everything: export the whole record in standard formats, and we restore it into a fresh system in front of you.

Your IT, privacy and vendor-risk reviewers receive the full architecture sheet before anything is installed.

Test results

Each result was measured on synthetic company data with known answers, so it can be checked. A pilot runs the same checks on your files.

579,140 of 579,140 source links verified. Every link from a figure back to its source file resolved, and none was broken. Synthetic finance data, October 2026.
368 of 368 figures matched. Answers that combined several systems matched the source database exactly. Synthetic finance data, October 2026.
0.9 seconds to add a ninth source. No rebuild was needed; 12 of 12 true matches were linked, and 6 of 6 look-alike names were kept apart. Synthetic test data, August 2026.
26 of 26 planted attacks contained. Instructions hidden in emails and files were quoted as content; in the 26 planted tests, none was followed. Synthetic finance data, August 2026.

How a pilot runs

A pilot takes one workflow your team repeats. We show DataBridge on a sample of your files, agree the scope and measures in writing, install it on your machines and measure against your baseline; then you decide what comes next.

It starts with a demo on a sample of your own documents and data.

Who we are

Dev Sirbhaiya: Co-founder; AI and Automation at Singlife · AI/ML Engineer at Neurowyzr · AI and Automation at Bajaj Finserv · Researcher, NTU-Schaeffler Lab · Tech Lead, NTU AI&ML Club · Director of Projects, MLDA@EEE.
Mehul Modi: Co-founder; Production AI agent over 16,000+ records at Changi's AI/ML Lab · Privacy-aware clinical AI at Neurowyzr · Multi-agent AI research at A*STAR.
Aaruni Garg: Co-founder; Research Intern at SEC · Architecture Intern at HighSpan, MAK Designs, TAS · Design Intern at WGS.
Ishaan Sirbhaiya: Co-founder; Real-time power-grid and industrial cybersecurity research at SUTD's iTrust Centre · Production full-stack systems at Bajaj Finance and across multiple client projects.

Walnut is backed by SUTD VIE's Baby Shark Fund. Walnut is based in Singapore.

How to reach us

Write to outreach@walnut.sg with one task your team does every week.