Accelerating (AI-supported) M&A due diligence insight in high-pressure merger transactions.
The context
M&A due diligence in connection with mergers or acquisitions represent the most time-critical and risk-intensive work in the legal profession. Representatives of the buyer receive access to a dataroom containing thousands of the target company’s files, mostly the contracts and the corporate housekeeping files of all group companies. The goal is to review all these documents to identify risks, liabilities and impediments to closing the transaction (such as change of control clauses, or non-assignment clauses in case of an asset-transaction).
The challenge
A challenge in M&A due diligence is the friction between speed and thoroughness. A team’s deadline for conducting the due diligence and writing a due diligence report is often immovable and short. Manually reviewing thousands of documents is physically impossible for a small team in the allotted time. Consequently, legal teams may resort to ‘sampling’ – reviewing only material contracts or the top 10% by value or TCV.
This approach leaves the buyer exposed to hidden risks in the unreviewed ‘long tail’ of contracts. Furthermore, a manual process is linear and resource-inefficient; senior attorneys waste expensive billable hours searching for basic clauses rather than analysing the strategic implications of the findings. Bottlenecks occur as the team struggles to triage which dataroom documents matter and which are irrelevant.
Contract deadline management:
Managing countless interdependent deadlines within construction projects is a complex task. As deadlines and their interdependencies evolve over time, it is challenging for the team to keep all stakeholders informed and prevent delays. Inconsistencies in contract amendments related to deadline changes increase the risk of disputes and negatively impact project timelines.
The negative consequences of contractual inconsistencies and unnecessarily complicated contract management are easy to spot in the frame of large construction projects.
The requirements
A modern due diligence solution must enable ‘total recall’ – the ability to review 100% of the documents in the data room, not just a sample. It must automatically categorise documents (separating Distributorship agreements from General purchasing agreements) and instantly extract key risk indicators. It needs to facilitate collaboration between different specialist teams (IP, Employment, Real property, Corporate) working on the same dataset.
Weagree's solution (Tabular review)
Weagree’s Tabular review solution is engineered to handle the volume and complexity of M&A transactions through robust project management and AI analysis.
- Umbrella projects for workstreams: you can create an ‘umbrella project’ for the entire transaction and organise the data room into subprojects for specific M&A-transactions, and within a dataroom for the various workstreams (e.g., ‘Project Apollo – Commercial contracts’, ‘Project Apollo – IP and licences’, ‘Project Apollo – Corporate housekeeping’). This keeps the review organised and secure.
- Rapid triage and filtering: upon upload of all files, the AI extracts the contract title, party details, its date, writes a brief description, and attempts to assign the contract sheet that fits the type of contract or file. This accelerates the intake of files significantly. The project dashboard provides a real-time overview of document counts per stage, allowing the lead partner to see exactly how far the review has progressed.
- Targeted risk extraction: You define the specific risks you are looking for – Change of Control, Assignment without Consent, Liability caps – each as a column in the contract sheet. You may even turn the review into the client’s complete CLM going forward. The AI runs a bulk analysis across all documents simultaneously. It doesn’t just find keywords; the AI reads the clause. For example, you can set a ‘Yes/No’ column for “Is consent required for assignment?” and the AI will populate it, reasoning its answer based on the text. You may as well anticipate two or three variants of no-assignment clauses (e.g. to capture and separate “consent not to be unreasonably be withed or delayed”). And if you hesitate, one click shows the relevant clause.
- Highlight critical or failing data. If the AI does not find data while you expected in the documents, this can be shown in the overview by a highlighted red field background. Also, if the AI finds certain metadata that are critical, a red-flag or suggesting high risk exposure, this can be shown by colourful tags in the overview.
- AI chat: For synthesis and summaries, the integrated AI Chat allows the team to interrogate the data. A lawyer can ask, “Which employment contracts contain golden parachute clauses exceeding 100k euro?” or “Which General purchasing agreements and Procured Services agreements protect against import tariffs?” and the AI will scan the extracted data to provide a summary.
The result
Weagree allows you to review the entire data room, not just a sample, significantly reducing post-transaction liability. In a major due diligence, for example, the reported initial review time was reduced by 65%. By automating the data extraction, your senior attorneys can focus entirely on strategic advice rather than data entry, delivering a comprehensive report faster and with greater confidence.
Other than a regular M&A due diligence, the extracted data and files are just one click to migration into a CLM. The data quality is high, which is crucial in nowadays contract lifecycle management. This prospect may tempt to collect many more (and some different) type of contract metadata, but that would be part of the same due diligence exercise.
How else does Weagree support M&A transactions?
Weagree is by its nature contract creation-oriented, with extensive DMS-capabilities, and as part of it Weagree contains functionalities specific for managing large projects like an M&A transaction:
- Involvement of multiple people (from varying expertise and interest: transaction leader, a law firm’s other departments, stakkeholders from client-side and maybe even those from the counterparty).
- Creating multiple inter-connected agreements (from NDA, info memorandum and Term Sheet or LOI, to a share purchase agreement, shareholders agreement, deeds of pledge and other security-related deeds or agreements, ancillary agreements, related closing documentation and powers of attorney).
- An in-app DMS that facilitates an easy processing of all transaction-related drafts and final versions.
- Tasks management, both on project level and on transaction-document level with clear to-do lists (viewing the others’ progress on task completion).
- Integration with your e-signing provider (for initiating, monitoring and reminding of all e-signatures) and automated processing of all e-signed transaction agreements.
Part of transaction management (but every user has their own overviews for the transactions in which they are involved) is Weagree’s semi-automated tasks management. On all individual contracts (or individual project documents) and the project-level Kanban boards, a user can monitor:
- all their own tasks and to-do’s
- the pending tasks of their direct colleagues
- the tasks in connection with a particular construction project, as well as in connection with individual agreements or documents of such project
- the tasks of one or more of their direct colleagues
In connection with every contract deadline and task, one or more e-mail notifications can be configured. This can be preconfigured by the admin (for the careless project managers) and tailored by the careful project leaders. Pending or overdue tasks are alerted by e-mail notification (and notification can be sent to colleagues, incl. supervising managers). Tasks can be recurring.
The task overviews are essentially also a ‘to do’ list for the project manager as well as a status report for the end-responsible management board. Hence, such to-do list (or pending tasks overview) can be exported in Excel-format.
Creating a dataroom in connection with an M&A due diligence entails the same activities and tasks as the migration (or post-merger integration) of the target companies would entail. While the vast part of such exercise is the collection of all contracts and related files from across the (target company) group’s organisation, as must be achieved for creating the M&A dataroom, once the files are collected, their migration into the acquiror’s CLM (Weagree or other) would follow the same stages as this M&A migration requires:
- Every file to be AI-analysed,
- AI-categorisation of the files by type of contract and the clustering of files that relate to a single business transation; followed by
- AI-powered data extraction, validation of AI contract review results; and
- Export of data and files.
