According to VentureBeat, London-based startup Ascentra Labs has raised a $2 million seed round led by Berlin VC firm NAP to automate survey analysis for consultants. Founded by former McKinsey & Company consultants, including CEO Paritosh Devbhandari, the company focuses exclusively on a niche within a niche: survey data crunching for private equity due diligence. The platform ingests raw survey files and spits out formatted Excel workbooks with traceable formulas, claiming to save early-adopter consultants 60 to 80 percent of their time on such tasks. Ascentra says it’s already working with three of the world’s top five consulting firms, though it can’t name them publicly due to the industry’s private nature. The funding round also saw participation from angel investors like Alan Chang, CEO of Fuse and former Revolut CRO, and Voi CEO Fredrik Hjelm.
The Niche is the Strategy
Here’s the thing: Ascentra’s entire bet is on extreme focus. The consulting world is a $250 billion beast, and everyone and their brother has tried to sell it some broad AI solution. They’ve mostly failed. So instead of trying to automate everything, Ascentra is going after one painfully specific, repeatable workflow. It’s a clever move. Private equity due diligence is standardized enough that the same analysis pops up deal after deal, making it automatable. And get this—Devbhandari claims even the biggest firms like McKinsey haven’t built internal tools for this. That means Ascentra isn’t competing against a homegrown tech stack; it’s competing against a junior associate’s willingness to pull another all-nighter in Excel.
Why Consulting is a Tougher Nut to Crack Than Law
This raises a big question. If AI is transforming legal work with companies like Harvey, why has consulting been so stubborn? Devbhandari’s explanation makes sense. First, the sales cycle is brutal. These firms move glacially on tech adoption, demanding insane security checks and references. But the bigger issue is technical. Legal work is largely text, which modern LLMs handle pretty well. Consulting? It’s a chaotic mix of PowerPoint, Word, and a million different Excel formats. Data is tabular, graphical, and textual all at once. Building a “multi-purpose agent” for that is a nightmare. So Ascentra’s approach of using AI (like OpenAI’s GPT models) just for the initial data ingestion and then relying on deterministic Python scripts for the actual number-crunching is probably the only way to get consultant buy-in. When billion-dollar deals are on the line, you can’t have a chatbot hallucinating a revenue projection.
The Real Barrier Isn’t Tech, It’s Trust
And that’s the core challenge: trust. Consultants live and die by the accuracy of their models. Devbhandari nailed it when he said even 95% accuracy isn’t good enough—they’ll just go back to the manual Excel they know. That’s why Ascentra’s output isn’t some black-box answer; it’s an Excel file with live, traceable formulas. The consultant can double-click a cell and see the math. That’s a brilliant design for this audience. It’s also why their early investment in certifications like SOC 2 Type II and ISO 27001 (and an upcoming audit for the new AI-specific ISO 42001) is so critical. It’s table stakes for even getting a pilot. Their per-project pricing model is another smart, trust-building move. It fits how consulting budgets actually work, bypassing central IT for an initial team-level tryout.
Automation Doesn’t Mean Elimination
So what does this mean for the future of consulting jobs? I think Devbhandari is right to push back on the idea that AI will just erase these roles. Look, automating the grunt-work of survey analysis doesn’t make the consultant obsolete; it changes their job. Instead of being a data-processing clerk, they can (theoretically) focus on higher-level strategy and insight. The industry will transform, but the human expertise—interpreting what the numbers *mean* for a deal—is still vital. The winners will be the firms and individuals who leverage tools like Ascentra to amplify their judgment, not replace it. For a sector that’s built on selling brainpower, that’s probably the only viable path forward. Now we’ll see if a focused, $2 million bet can actually start to shift a quarter-trillion-dollar industry.
