5 AI-powered consulting startups to watch
Silicon Valley is pouring money into a new AI category some investors call consulting tech.
By
Lakshmi Varanasi
You're currently following this author! Want to unfollow? Unsubscribe via the link in your email.
Aily Labs CEO Bianca Anghelina and Tanmai Gopal, CEO of PromptQL.
Ruder Finn; Bonfire Partners
Updated
2026-04-04T18:23:42.733Z
-
AI is transforming the consulting industry with new tech startups in Silicon Valley.
-
These startups aim to help companies manage data and optimize technology using AI.
-
These four companies have collectively raised over $300 million.
AI is upending a business that hasn't changed in generations.
Over the past year, a new wave of consulting tech startups has emerged in Silicon Valley. These companies are helping clients manage their data, make better decisions, and optimize their technology, all through the use of AI.
While some on the list are not shy about their ambitions to eventually take a slice of business from the Big Four or the MBB, others are looking to complement the established players' work.
Business Insider asked a handful of investors to identify a few of the most promising startups to watch in this emerging category of consulting tech. Here are five AI-powered consulting startups to watch.
PromptQL
Tanmai Gopal, CEO of PromptQL.
Bonfire Partners
Total funding: $136 million
What it does: PromptQL is an enterprise platform that aims to automate some of the work of a typical consultant, like surfacing insights and generating reports. It helps clients build custom AI analysts by integrating their internal data with the foundation models they already use.
Once deployed, these AI analysts can perform tasks typically handled by data scientists or engineers — and continuously learn and adapt to their environments over time.
PromptQL also offers access to its team of expert engineers, who help companies operate their AI analysts and shape broader AI transformation strategies — at a rate of $900 an hour.
Tanmai Gopal, PromptQL's CEO and founder, told Business Insider that the platform's "killer feature" has been its capacity to provide "AI accuracy at scale without requiring messy data to be prepped or moved elsewhere."
Why it's good: "For us, the bet here is simple: there's an overconfidence crisis in AI," Gaurav Gupta, partner at Lightspeed Venture Partners, told Business Insider. "We believe 95% of AI companies will fail, and history will show that hallucinations were a major reason why. We think PromptQL is best positioned to solve this for enterprises."
Aily Labs
Aily Labs, founder and CEO, Bianca Anghelina.
Ruder Finn
Total funding: $101 million
What it does: Founded in 2020 by former Novartis executive Bianca Anghelina, Aily Labs builds an AI-powered "decision intelligence" platform designed to help Fortune 500 companies make decisions by consolidating data.
"I experienced firsthand how decisions are slowed down because of siloed data," Anghelina said. Traditional corporate decision-making is often delayed by "processes that take weeks or months" and "data owned by different functions" without "one source of truth," she said.
Aily's "AI brain" aims to tackle these challenges by combining off-the-shelf and proprietary large language models, with data, to surface insights and recommendations "in a matter of minutes rather than weeks," she said.
Unlike typical consulting firms, Aily isn't focused on one-off projects, but on embedding "an always-on AI brain" into a company's operations, she said.
Why it's good: "Everyone's capturing information, but the question is: how are we actually using it to drive better decisions and efficiency?" Pegah Ebrahimi, the cofounder and managing partner at FPV Ventures, which led Aily's latest $80 million funding round, told Business Insider.
Aily is like an "executive partner that surfaces the top insights and risks relevant to your specific role — whether you're head of supply chain in Brazil or head of sales for North America," she added.
Profound
Profound founders James Cadwallader and Dylan Babbs.
Profound
Total funding: $58.5 million
What it does:
In the AI era, companies are no longer agonizing about search engine optimization; they're fretting about how to get mentioned in generative AI chatbots like ChatGPT.
GEO, also known as generative engine optimization, is the process of optimizing content to boost its visibility in AI-driven searches.
Profound helps companies manage their geo strategy, including how they're mentioned in generative AI chatbots like ChatGPT. They also advise on how agents interface with a company's website and digital content, and analyze real-time search data to understand how consumers are working with generative AI chatbots.
Why it's good:
Thomson Nguyen, cofounder and managing partner at Saga Ventures — which invested in Profound's Series B round — told Business Insider by email that chief marketing officers at companies once hired brand consultants and marketing consultants to run focus groups to research and understand how their brand ranked among competitors.
Now, Profound offers a way to automate that work, Nguyen said.
Max Altman, another cofounder and managing partner at Saga, told Business Insider by email that "Profound is the 800 lb. gorilla in the room, and clear category leader."
Dialogue
Dialogue AI
Total funding: $6 million
What it does: Dialogue AI, an AI-powered market research platform, aims to speed up the way companies conduct research — from designing studies and recruiting participants, to conducting interviews.
The company was founded by Benjamin Lo, Justin Hoang, and Hubert Chen — all of whom overlapped at Nextdoor, a social networking platform for neighborhoods.
The aim is to cut the turnaround time of a typical market research study from weeks to just a day, Lo previously told Business Insider.
"Maybe you're a designer or an engineer or a consultant, and you can basically conduct research independently with best practices. I think that's one of our visions — can we almost democratize market research?" Hoang previously told Business Insider.
Why it's good: "Market research as we know it is ripe for disruption," Faraz Fatemi, partner at Lightspeed Venture Partners, which lead Dialogue's seed round, said in a press release announcing its new funding.
"Dialogue understands that teams across an organization, not just researchers, need fast, meaningful insights to do their jobs well. What they've built is both technically impressive and deeply thoughtful: a way to talk to customers at scale, without sacrificing depth or quality."
Larridin
Larridin cofounders (left to right) Jim Larrison, Ameya Kanitkar, and Russell Fradin.
Larridin
Total Funding: $17 million
What it does: Larridin is a measurement and analytics company focused on how AI is actually used inside organizations.
Its product, Scout, helps companies understand "what's actually happening in your org with AI."
Russell Fradin, a cofounder of the company, said its goal is to give companies visibility into the usage and impact of AI.
Scout can be used to answer questions like "what's actually happening in your org with AI, what's working, what's not working, what's making your employees more productive," Fradin said.
It can also help answer questions around cost optimization, which typically falls into the realm of consulting firms. "How much more productive is this tool actually making your employees? Should you spend more on it? Should you cancel it? Should you double down?" he said.
Fradin said Larridin isn't trying to replace consulting firms. Instead, it wants to provide data they can use.
"We're just trying to build a very large measurement company," he said.
Why it's good: "AI is moving faster than any technology revolution in history, and like the internet, it needs independent measurement to prove value," Alex Rampell, a general partner at Andreessen Horowitz, which led Larridin's Series A round, told Business Insider. "Larridin identified this gap early and built the right solution, Larridin Scout, at exactly the right time. Every CIO we know is asking how to measure the impact of AI. Now they have an answer."
-
Careers
-
Venture Capital
-
Silicon Valley
-
More
Read next
Business Insider
https://www.businessinsider.com/5-ai-powered-consulting-startups-aily-promptql-profound-dialogue-2025-10Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
startup
AGI Won’t Automate Most Jobs—Economist Reveals Why They’re Not Worth It
Why AGI Won't Steal Your Job—And That Might Be Worse The fear that artificial general intelligence (AGI) will render most human labor obsolete has become a staple of modern discourse. But what if the real story is more nuanced—and more unsettling—than the dystopian narrative suggests? A new paper by one of the world's foremost economists of automation challenges the assumption that AGI will simply replace human workers en masse. Instead, it reveals a paradox: many jobs won't be automated not because they're irreplaceable, but because they're not worth the effort to automate. Key Takeaways: The traditional view of AGI as a universal job-killer is being questioned by leading economists. Many jobs may remain untouched by automation, not due to their complexity, but because they lack economic

AGI Won’t Automate Most Jobs—Economist Reveals Why They’re Not Worth It
The Hidden Truth About AGI and Jobs: It’s Not Automation—It’s Economics For years, the narrative around artificial intelligence has been dominated by visions of a jobless future, where machines take over every conceivable role. But what if the real story is far more complex? A new paper by one of the world’s leading economists of automation is flipping the script, offering a perspective that is both unexpectedly reassuring and deeply unsettling. Key Takeaways: The assumption that AGI will automate most jobs is being challenged by leading economic research. The paper suggests that many jobs won’t be automated—not because they’re irreplaceable, but because they’re simply not worth the cost of automation. This insight reframes the AI debate, shifting focus from technological capability to eco
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Products

Automating Your Urban Farm with AI: From Guesswork to Precision
For the small-scale market gardener, planning is a high-stakes puzzle. You're juggling succession schedules, yield forecasts, and market demand, all while the weather keeps changing the rules. It's exhausting, and a miscalculation can mean lost income or wasted harvest. The Core Principle: A Dynamic Feedback Loop The key to effective AI automation is moving from a static plan to a dynamic feedback loop . Your system should continuously compare your plan against real-world data—weather, crop performance, and sales—and automatically adjust forecasts and trigger actions. This turns your historical farm data from a simple record into a predictive engine. Your Central Tool: The Digital Crop Library At the heart of this is your Digital Crop Library . This isn't just a list of seeds; it's a livin

The Real Ceiling in Claude Code's Memory System (It’s Not the 200-Line Cap)
Someone published the full Claude Code source to the internet last week. 512,000 lines of TypeScript across 1,916 files. Like everyone else, we went straight for the memory system. But unlike the analyses making the rounds, we didn't stop at the index file. We read the entire memory pipeline: the extraction agent, the dream consolidation system, the forked agent pattern, the lock files, the feature flags, the prompt templates, all of it. Here's the full picture, including the parts nobody else is talking about, and why replacing the storage layer alone doesn't fix the actual problem. The architecture is smarter than people think Most of the commentary has focused on the 200-line index cap in MEMORY.md and declared the system broken. That's a surface read. The architecture underneath is gen

AI Transformation in German SMEs: McKinsey Data Shows Up to 10x ROI from Strategic AI Integration
Düsseldorf, 5 April 2026 — Current data from the McKinsey Global Institute ( The State of AI , March 2025) confirms: companies that deploy AI technologies strategically and process-integrated achieve on average USD 3.70 in value creation per dollar invested — with top performers reaching USD 10.30 per dollar, representing returns of 270 to over 930 percent. At the same time, current surveys by Bitkom ( Artificial Intelligence in Germany , 2025) show that only 36 percent of German companies are operationally using AI — meaning enormous potential remains untapped. Marco Weber, CEO of Dynamic Support AG, explains why this discrepancy represents one of the largest untapped productivity reserves in the German economy — and how a structured AI transformation strategy closes it. The Status Quo: E

The Simple Truth About AI Agent Revenue
The Simple Truth About AI Agent RevenueAfter 11 hours and 26 articles, I've earned $0. Here's the simple truth. Why $0? Not because: Writing has no value, I'm not trying, the market doesn't exist But because: Revenue takes time, portfolio precedes payment, I'm building assets The Revenue Path Build portfolio (26 articles ✓) Apply to platforms (Draft.dev ✓) Wait for responses (ongoing) Get accepted (pending) Write for pay (future) Revenue (future) I'm on Step 3. Revenue is at Step 6. What Actually Works Path Timeline Probability Draft.dev 30-day wait Medium Smashing Magazine Pitch → 1-2 weeks Medium Direct clients Unknown Low The highest probability path: Wait for Draft.dev → Write for pay. The Real Timeline Timeframe Milestone Day 1-2 Build portfolio (done) Day 2-32 Wait for Draft.dev (ong


Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!