Legal Due Diligence API for M&A, KYB and Counterparty Screening

Use Case · Due Diligence API

Updated for 2026 · Claw Editorial

A single manual court search takes a few minutes when it works. Multiply that by every promoter, director, and group entity in an M&A deal, or every business signing up on a lending platform, and manual search stops being an option. This is the problem a legal due diligence API is built to solve: turning litigation and party-level risk checks into something a system can call automatically, at volume, rather than something a person has to do by hand on a court website. This guide explains where that API fits in three different workflows, mergers and acquisitions, KYB onboarding, and counterparty screening, and what to look for before you build on one.

01Why due diligence needs to be an API, not a search box

Legal due diligence, done manually, is a person opening a court website, typing in a name, reading through results, and writing down what they find. That works for one company, checked once. It breaks down the moment the job has scale, repetition, or a deadline attached to it.

Manual court searches do not scale

An M&A deal rarely involves just one entity. There is the target company, its subsidiaries, its promoters, and often its key directors, each of whom needs an independent litigation check across the Supreme Court and the relevant High Courts. Done by hand, that is dozens of separate searches per deal, each one dependent on a person typing the name correctly and reading the results carefully. See how to track cases across all Indian courts for why this is already hard for a single entity, before multiplying it by a deal team.

Onboarding decisions cannot wait days for a search

A lender, NBFC, or marketplace onboarding a new business does not have days to spare on a manual litigation check. The onboarding decision, or at least the risk flag that routes a file to manual review, needs to happen in the same session as the application. That is only possible if the litigation check is a call an onboarding system makes automatically, not a task a compliance analyst does separately later.

Risk does not stop at onboarding

A counterparty that was clean at onboarding can pick up litigation a year into the relationship. A vendor, franchisee, or borrower needs to be checked again periodically, not just once at the start. A one-time PDF report from a due diligence exercise cannot do this. It needs a system that can be queried again, or that can push an alert when something new appears.

The question is no longer whether the case exists on a court website. It is whether your system can find it automatically, at the speed and scale your business actually runs at.

02Three jobs that need this data

Legal due diligence API demand mostly comes from three different jobs. They look similar on the surface, litigation checks against a name, but they run on different triggers and need different treatment.

M&A and pre-investment diligence

Here the API is used to run litigation searches against the target company, its group entities, and its promoters and directors, as part of a wider due diligence exercise. The output usually needs to feed into a due diligence report or a virtual data room review, alongside corporate and contract findings.

KYB (know your business) at onboarding

Lenders, NBFCs, and marketplaces that onboard businesses need to check whether an applicant, or its promoters, have material pending litigation before approving them. See legal due diligence before lending for banks and NBFCs for how this fits into a credit or onboarding decision. The check has to run inside the onboarding flow itself, automatically, rather than as a separate manual step that slows the applicant down.

Counterparty and vendor screening

Procurement, franchise, and credit risk teams need to periodically recheck the businesses they already deal with, not just screen them once. Vendors can pick up disputes, borrowers can be sued, franchisees can end up in consumer forums. For the tooling around ongoing monitoring, see the best tools for tracking cases beyond NJDG.

03What the API actually needs to deliver

A litigation data feed that just returns a list of case titles is not enough for any of these three jobs. A legal due diligence API needs to get several things right at once.

• Structured output: results as data your system can parse and route (case number, court, status, parties), not a PDF or a page of unstructured text someone has to read.
• Reliable name matching: Indian names and company names are spelled inconsistently across filings. A search that only matches an exact string will miss real cases. Matching needs to tolerate misspellings and near-variants, sometimes called proximity or phonetic matching.
• Broad court coverage: a check that only covers one court is not a real due diligence check. At minimum, the Supreme Court and the relevant High Courts need to be covered, since a counterparty can be sued anywhere it operates.
• Batch capability: the ability to check many names at once (a portfolio of borrowers, a list of directors) rather than one lookup at a time, since this is where manual search fails hardest.
• Speed: fast enough to sit inside a live onboarding decision, not just a batch job that runs overnight.
• Verifiable citations: a result that cannot be traced back to a real, citable case is not usable in a due diligence report or a regulatory file. The output should point to a verifiable source, not just an AI summary.
• A way to flag ambiguous matches: common names will produce multiple possible matches. The API, or the workflow around it, needs a way to route uncertain matches to a human reviewer rather than silently picking one.

04Court records vs corporate records: two different data sources

A common mistake is treating "due diligence data" as one thing. In practice it comes from two different kinds of sources, and most platforms are strong in one and weak in the other.

Court records cover litigation: pending cases, orders, and judgments against a party, held by the courts and tribunals themselves. This is what tells you whether a company or a person is being sued, or has sued someone else.

Corporate records cover a business's registered filings: incorporation details, directors, shareholding, charges, and financial filings, typically sourced from the Ministry of Corporate Affairs and related registries. This is what tells you who actually owns and controls a company, and whether its assets are encumbered.

A full KYB or M&A check usually needs both, and they rarely come from the same vendor with equal depth. For a closer look at how these two data sources differ and where each one is strongest, see corporate records vs court records for vendor due diligence. Treat court-record coverage and corporate-record coverage as two separate checkboxes when you evaluate a provider, not one.

05How to integrate it into your workflow

The value of an API is in where it sits, not just what it returns. A few integration patterns come up repeatedly.

Inside the onboarding or loan origination flow

For KYB, the litigation check is called as one step in the applicant's onboarding journey, alongside identity and financial checks, so a flag can route the file to manual review before approval rather than after.

Inside the due diligence or data-room review tool

For M&A, the check is usually run in batch against a list of entities and individuals compiled from the deal structure, with results feeding into the due diligence report rather than a standalone document.

As a scheduled or event-driven recheck

For counterparty screening, the pattern is different: a periodic recheck job, or an alert-based approach where the system is notified when something changes for a monitored party, rather than a one-off lookup.

Build a review queue for uncertain matches

Whatever the workflow, plan for the fact that not every match will be clean. A sensible integration routes high-confidence matches automatically and sends ambiguous ones (common names, partial matches) to a human reviewer, rather than treating every API response as a final answer.

06What to check before you commit

Before building a workflow around a legal due diligence API, it is worth checking a few things directly with the provider, since these vary a lot between vendors.

• Court coverage: which courts and tribunals are actually covered, and for what date range.
• Whether it is search-only or also tracks ongoing status: a one-time search is different from a service that can keep monitoring a party over time.
• Data freshness: how often the underlying index is updated.
• Output format: structured, machine-readable results versus a document you still have to read manually.
• Batch support: whether you can submit a list of names in one call, which matters for both M&A and portfolio-wide counterparty screening.
• Pricing model: per-lookup, subscription, or seat-based, and whether it fits how often you actually need to run checks.

To go deeper on the M&A workflow this data feeds into, see what legal due diligence is and how to do litigation due diligence.

07Where Claw fits

Claw is an all-in-one legaltech platform for Indian advocates, law firms, and corporate legal teams, combining AI-based case search, an AI legal assistant (Legal GPT), case management, and compliance automation across all Indian courts and tribunals. Claw also offers a live public and partner API for programmatic access to court and litigation data, which is the piece that matters for the three jobs described above.

For M&A and pre-investment diligence, the API sits on top of Claw's case search: 30 crore judgements across 25 High Courts (1980 to 2026) and the Supreme Court (1950 to 2026), with results in under 5 seconds and verified, court-ready citations. This lets a deal team or diligence tool run litigation checks against a target and its promoters programmatically, instead of searching each court separately.

For KYB at onboarding, the same search layer can be called as part of an applicant screening flow, with name-tolerant matching designed to catch misspelled or near-variant names, which matters when the applicant data itself is not always clean.

For counterparty and vendor screening, Claw's case management layer tracks matters across 8,200+ courts, including tribunals and district courts, so a monitored party is not just checked once but can be followed over time, with automatic updates and alerts as the underlying case management product already does for tracked matters.

On data handling: Claw does not use customer case documents to train AI models. For teams running sensitive M&A or counterparty data through an API, that is worth confirming directly with any vendor before integrating, Claw included.

For more on the two workflows this page touches, see legal due diligence before lending for banks and NBFCs and the best tools for tracking cases beyond NJDG.

08Frequently asked questions