For years, the consulting world has remained an outlier in the AI revolution, stubbornly relying on manual, time-consuming processes while other industries automated. Now, a London-based startup, Ascentra Labs, has raised $2 million in seed funding to change that, starting with the most painful bottleneck: endless hours spent wrestling with Excel spreadsheets.
The Problem: Consultants Still Stuck in Spreadsheet Purgatory
The global consulting industry, worth $250 billion, has largely resisted the AI surge seen in law and accounting. While firms like Harvey have disrupted legal work with AI, consultants still spend countless nights manually analyzing survey data, a core component of private equity due diligence. This isn’t just an inefficiency; it’s a drag on productivity and a source of frustration for even the most elite firms.
Ascentra Labs, founded by former McKinsey consultants, is betting that focused automation can break through this resistance. Their platform ingests raw survey data and outputs fully formatted Excel workbooks with traceable formulas—a task that typically consumes junior associates’ time.
Why Now? The Unique Challenges of Consulting AI
The disparity between AI adoption in law versus consulting isn’t accidental. Unlike legal work, which largely deals with text, consulting involves a mess of data types: spreadsheets, presentations, documents. This complexity has blocked broader AI solutions.
“You can have multiple formats of Excel in itself,” explains Ascentra CEO Paritosh Devbhandari, a veteran of McKinsey’s AI division. The firm’s success hinges on solving this, not with a general AI agent, but with a hyper-focused tool for one specific workflow.
Strategy: Private Equity Survey Analysis as a Beachhead
Ascentra isn’t trying to automate all consulting work at once. Instead, it’s targeting private equity survey analysis—a standardized, repeatable task. This allows the company to sidestep the broader technical challenges of automating unstructured consulting engagements.
The company claims three of the top five consulting firms already use its platform, reporting 60-80% time savings. However, client confidentiality prevents public naming, adding a layer of secrecy to its early traction.
Accuracy is Existential: Avoiding AI Hallucinations in High-Stakes Deals
For AI in quantitative workflows, precision is non-negotiable. Consultants advising on billion-dollar investments can’t afford errors. Ascentra addresses this by blending AI with deterministic Python scripts: GPT models handle data ingestion, but the actual analysis is performed by code that produces verifiable outputs.
“Consultants require a very, very high degree of fidelity,” Devbhandari says. “Even if it’s 95% accurate, they will revert to Excel because they know it, they trust it, and they don’t want there to be any margin for error.”
Enterprise Security and Per-Project Pricing
Selling to consulting firms requires enterprise-grade security certifications (SOC 2, ISO 27001) which Ascentra has secured. The company also uses a per-project pricing model instead of subscriptions, aligning with how consulting firms allocate budgets. This approach may ease adoption by bypassing central IT procurement, but introduces revenue uncertainty.
The Future of Consulting: Transformation, Not Elimination
Ascentra’s founders believe AI won’t eliminate consulting jobs, but will fundamentally reshape them. The shift will likely reduce repetitive tasks and empower consultants to focus on higher-level strategy.
“People love to talk about how AI is going to remove the need for consultants, and I disagree,” says Devbhandari. “Yes, the role will change, but I don’t think the industry goes away.”
Ascentra plans to use the funding to expand in the U.S., where most of its customers are based. The startup now faces the challenge of converting pilot programs into lasting enterprise contracts while competing with larger, better-funded firms that will inevitably enter the space.
The irony is striking: after years advising Fortune 500 companies on digital transformation, consulting may finally have to adopt it for itself.
