A due diligence deadline doesn't wait for a target company to finish cleaning up its Excel files. That's usually where ESG assessments stall: not because the data doesn't exist, but because nobody has time to extract, format and upload it before the deal team needs an answer. AI copilots and agents are built to close exactly that gap.
Why traditional ESG due diligence slows deals down
Most ESG data tools stop at a chatbot: they answer questions about data that has already been entered. The real bottleneck sits upstream, in getting a target company's consumption data, supplier records and site information into a usable format in the first place, usually inside a short due diligence window.
What makes an AI agent different from a chat
The distinction matters for how fast a fund can move:
- Copilots answer questions: once data is in the system, Manglai's copilot lets deal teams ask direct questions about a company's emissions, footprint or trends in plain language, without waiting for a custom report.
- Intelligent import removes the reformatting step: Manglai's AI already reads invoices in PDF, Excel or supplier formats, extracts consumption, classifies it by scope and assigns it to the right site, across countries, languages and currencies.
- Agents execute tasks: the next step, which Manglai's artificial intelligence page lists as coming soon, is agents that read an Excel file, transform the data and upload it to the platform autonomously, chaining several steps without a person intervening at each one.
Applying AI across a multi-company portfolio
The same tools that speed up due diligence on a single target keep working after the deal closes. As discussed in the webinar Investing with impact: carbon measurement for private equity with Columna Capital, the real gain isn't a one-off audit but being able to repeat the same measurement process for every company added to the portfolio, without rebuilding it each time.
From due diligence to ongoing portfolio monitoring
After onboarding, the same AI layer supports continuous monitoring: it flags data gaps, keeps every portfolio company's footprint on the same standard and feeds directly into the value creation levers ESG compliance can unlock, from financing terms to operational savings. For the wider picture of what AI does in ESG management, see the role of AI and technology in modern ESG management.
For GPs who need diligence-grade carbon data on a deal timeline rather than a consulting timeline, Manglai's platform for investment funds is built around exactly that constraint.
