The AI-first digital engineering company that treats machine learning as an engineering discipline - and has spent a decade closing the gap between the demo and production.
Most enterprise AI projects do not fail because the math is wrong. They fail in the gap between a convincing demo and a system that runs every day inside a regulated business. Quantiphi, founded in 2013, built an entire company to live in that gap. It calls itself an AI-first digital engineering firm, which is a precise way of saying it does the unglamorous work - data pipelines, document parsing, model deployment, compliance - that turns a promising model into something a bank or a hospital can actually use.
The founders - Asif Hasan, Vivek Khemani, Reghu Hariharan and Ritesh Patel - came out of Philips Healthcare and Capgemini with a shared conviction that AI would reshape how businesses operate. They spent the company's early years largely bootstrapped, taking on client work and reinvesting, before raising a small Friends & Family round in 2018 and a first institutional round from Multiples Private Equity in December 2019. That bootstrapped habit - build what customers will pay for - shows up in the product portfolio the company would later ship.
Today Quantiphi employs roughly 3,500 or more people across six continents, and it has become one of the most-awarded partners in the two cloud ecosystems that matter most for AI: Google Cloud and AWS. It works across financial services, insurance, healthcare and life sciences, retail, media and gaming, telecom and the public sector - anywhere large, regulated organizations need production-grade AI rather than a proof of concept.
Strip away the jargon and Quantiphi sells two things that reinforce each other: engineering services and software products. On the services side, teams build machine learning systems, decision-science models, data platforms and cloud infrastructure - typically on Google Cloud, AWS or Azure. On the product side, years of repeated client work have hardened into reusable software.
Its customers are large enterprises with a common frustration: they have data, they have a use case, and they cannot get a model reliably into a workflow that auditors, regulators and operations teams will accept. An insurer wants to stop paying people to read policy documents by hand. A lender wants faster, consistent underwriting. A hospital system wants to mine clinical records without breaking compliance. A retailer wants personalization that survives contact with real inventory and real fraud.
These are not research problems. They are integration, reliability and governance problems - which is why Quantiphi frames itself as an engineering company first and a consultancy second. Responsible AI, in that context, is not a marketing line. When you build models for insurers and hospitals, transparency and compliance are part of the deliverable.
An enterprise-ready generative AI and search stack that lets organizations own their GenAI pipeline - searching internal knowledge, synthesizing it, and automating downstream tasks with enterprise controls.
AI-enabled document management aimed at insurance and lending. It automates the end-to-end policy review process for carriers, brokers, third-party administrators and lenders - cutting the manual reading grind.
An AI-powered coding agent built to speed the software development lifecycle while keeping enterprise-grade security intact - Quantiphi's bet on agents inside the enterprise SDLC.
Machine learning, decision science, big data integration, business intelligence and cloud data-platform engineering delivered across the major hyperscalers.
Business and technology advisory, migration, MLOps and AI-first digital engineering frameworks for enterprises modernizing on the cloud.
Industry-specific accelerators for finance, insurance, healthcare and retail - so delivery starts from a domain baseline rather than a blank page.
Plenty of firms now claim to "do AI." Fewer get named Google Cloud Partner of the Year in four categories in a single year, as Quantiphi did in 2025 - including AI Partner of the Year for North America. That kind of recognition is noise unless it maps to work that actually shipped, and cloud vendors hand out these awards based on delivered customer outcomes.
Quantiphi's core differentiator is depth in a small number of ecosystems rather than a scattershot presence everywhere. It went all-in on the hyperscalers - Google Cloud, AWS, NVIDIA and the modern data platforms around them - and became one of their most-certified, most-awarded partners. In a market where the underlying models are increasingly commoditized, the moat is the integration expertise and the trust of the platform.
The company sits in a crowded field. It competes with global consultancies and system integrators - Accenture, Deloitte, Slalom, Thoughtworks - and with focused analytics firms like Fractal Analytics, Tiger Analytics and LTIMindtree's AI arms. What separates Quantiphi is the services-to-software flywheel: it turns repeated delivery patterns into products, then uses products to make the next delivery faster.
Where does it fit in the market? Squarely in the enterprise AI-services layer that sits between the cloud platforms below and the business problems above. It is the firm you hire when the model is the easy part and getting it into production, compliant and reliable, is the hard part.
Partner of the Year in four categories, including AI Partner of the Year for North America.
Global Partner of the Year, Consulting category winner; Collaboration category finalist.
Partner of the Year in three categories for solutions and customer innovation.
Recognized as a 4X AWS Partner of the Year across regions and categories.
Four co-founders from Philips Healthcare and Capgemini start the company on the belief that AI will transform business.
Raises a Friends & Family round after years of running largely bootstrapped.
Closes its first institutional round (~$20M) from Multiples Private Equity.
Rolls out AI-enabled document processing aimed at insurance and lending.
Introduces an enterprise generative AI platform as demand for LLM solutions surges.
Wins three Google Cloud categories; launches the Codeaira coding agent.
Named 2025 Google Cloud Partner of the Year in four categories and an AWS global Consulting winner.
Quantiphi's funding history is unusual for a company of its size. Where many peers raised aggressively, Quantiphi took a Friends & Family round in 2018 and a single institutional Series A of about $20M from Multiples Private Equity in December 2019 - a total of roughly $23-24M across two rounds. Much of its growth was funded by the business itself.
Revenue figures reported by third-party trackers vary widely, from around $200M to as high as $1.7B annually depending on the source and year. As a privately held company, Quantiphi does not publish audited figures, so those numbers should be read as estimates rather than confirmed results.
"Quantiphi" blends quantify with the Greek letter phi - a nod to using data and mathematics to quantify business impact.
The company ran largely on its own revenue for roughly five years before taking outside institutional capital.
Dociphi targets one of insurance's least glamorous, highest-value tasks: reading policy documents so people do not have to.
Two of the founders came from Philips Healthcare - part of why regulated-industry AI is in the company's DNA.
Explore Quantiphi's talks, customer stories and product walkthroughs on its official channel.
It is an AI-first digital engineering company that builds cloud, data engineering and machine learning solutions for enterprises, plus its own AI products - Baioniq, Dociphi and Codeaira.
It was founded in 2013 by Asif Hasan, Vivek Khemani, Reghu Hariharan and Ritesh Patel, who previously worked at companies including Philips Healthcare and Capgemini.
In Marlborough, Massachusetts, with delivery and office locations across six continents.
Google Cloud, AWS and NVIDIA are core partners. Quantiphi is a multi-time Google Cloud and AWS Partner of the Year.
Baioniq (enterprise generative AI platform), Dociphi (intelligent document processing for insurance and lending) and Codeaira (an AI software-engineering agent), alongside its consulting services.