BUILD INTELLIGENT
SOFTWARE PRODUCTS FASTER

Manifold is a leading AI engineering services company.
Global companies partner with us to build intelligent software products faster.

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Exceptional

Our team members join us from leading tech companies, venture-backed startups, and elite universities.

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Trusted

We are trusted by CTOs at global companies to help them get from business case to production software.

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Experienced

Our approach to every collaboration is based on decades of collective experience launching software, data, and AI products.

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Recognized

We are regularly invited to speak at industry events and are featured in a variety of publications.

"Manifold achieved in 3 months and a team of 4 what could have taken 12 months and a team of 10. They have a unique ability to navigate the maze of product and architecture decisions for AI products."

— SVP TECHNOLOGY 
GLOBAL 500 ELECTRONICS

Unique AI, Data & Software Engineering Team

Our team members join us from leading tech companies, venture-backed startups, and elite universities. Meet some of our engineering leaders.

Profile
Vinay Seth Mohta

Chief Executive Officer

  • CTO, CISO, Co-Founder, Kyruus
  • Product Manager, Kayak
  • CTO, Global Health Delivery 
  • Architect & Product Manager, Endeca Technologies
  • Developer, The MathWorks
  • Multiple patents (text search, faceted navigation)
  • MEng & BS, EECS – MIT

Profile
Sourav Dey

Chief Technology Officer

  • Staff Engineer, Google
  • Principal Data Scientist, AutoGrid
  • Principal Engineer, Ingenu
  • Senior Engineer, Qualcomm
  • Multiple patents (intrusion detection, user similarity, wireless)
  • PhD, MS & BS, EECS – MIT

Profile
Wassaf Farooqi

Director, Engineering

  • VP Engineering, Kyruus
  • Software Engineer, HubSpot
  • Software Engineer, EMC
  • BS, Computer Engineering – Northeastern University

Profile
Rajendra Koppula

Director, Machine Learning

  • Staff Engineer, 3G/4G Cellular Group, Qualcomm
  • MS, Statistics & MS, EE – Northern Illinois University; BS, EECS – Osmania University

Profile
Jakov Kucan

Senior Architect, Data Engineering

  • Chief Architect, Kyruus
  • Director of Product Strategy, PTC Mathcad 
  • Software Architect, Mathsoft
  • Co-founder/Engineer/Architect/V.P. and Chief Scientist, Centive
  • PhD, Computer Science – MIT; MA, Mathematics, BSE, Computer Science and Engineering – UPenn

Profile
Rachel Lomasky

Director, Machine Learning

  • Co-founder and Chief Data Officer, Wevo Conversion
  • Analytics Director, Opera Solutions
  • PhD, Machine Learning – Tufts University; BA, Computer Science – Wellesley College

Profile
Alexander Ng

Director, Infrastructure & DevOps

  • DevOps Tech Lead, Kyruus
  • Software Systems Engineer, MITRE
  • Software Systems Engineer, US Navy
  • BS, EE – Boston University

Profile
Ramesh Sridharan

Architect, Machine Learning

  • Head of Machine Learning, Vidado (formerly Captricity)
  • Course Instructor, Data 8, UC Berkeley
  • Volunteer Computer Science Instructor, meet (Middle East Entrepreneurs of Tomorrow)
  • PhD, EE and CS, MS, EE and CS – MIT; BS, EE and CS – UC Berkeley

Profile
Matyas Tamas

Director, Data Science

  • Head of Supply Data Science, Uber
  • Founder of Data Science team, Quora
  • BS, Physics – Caltech

Today, software is eating the world. It is a new plane of competition across industries, not the back office function it once was. When choosing a team to partner with, it's good to ask: Would a Silicon Valley venture investor partner with this team today?
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GOT SOMETHING IN MIND?

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AI Isn't Magic

AI and machine learning aren't magic, but rather a set of tools that can enable new capabilities. It's important to start with relevant business strategy and go-to-market questions.

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Escaping AI Jargon

We try to dial back on the "pixie dust" aspect of AI, and look at our client projects within the context of a more traditional product development spectrum.

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10x Engineering

Software product development is often described as a maze—a decision maze of both product-market and technology choices. A 10x engineer makes good judgments in navigating that decision maze.

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Mathematical Modeling Beyond Machine Learning

The hype around ML makes it easy to forget about more tried and true mathematical modeling methods, but they are complementary tools in a larger toolbox.

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WHY MANIFOLD