Accelerate your AI ambitions
Unparalleled AI Innovation and Expertise Within Reach. Driven by Visionary Professors and Entrepreneurs Who’ve Elevated Their Ventures Above $200 Million
It's like Silicon valley in a box
A team of AI Ph.D.s and industry experts analyze your business needs and identify AI-driven acceleration opportunities
Full-stack development of AI experiences by a team experienced in launching AI products for 20+ million users
Reliable deployment and hosting services in both public and private clouds
Use case: Conversational AI, private/customized chatGPT, etc.
5x-23x
“A lot of the customers I’ve talked to are unhappy about the cost that they are seeing for running some of these models,”
– Adam Selipsky, CEO, Amazon Web Services
Want your own customized AI solutions and worry about cost, privacy, or development timeline?
5x - 23x cost reduction - compared to typical Open AI (LLM) deployment
3 month - short timeline from idea to production
Customized GPT- AI products customized based on your data and needs
Privacy - You own private language models without reliances on OpenAI or external APIs
IP and Patent - own your AI solution IP and AI patents
"Imagine a world…where you don’t need AI expertise or an army of developers to build remarkable AI experience and products"
CASE STUDY
CUSTOMER CASE STUDY 01: POCKETNEST
The experience was phenomenal. The unique ability to have the vision, have the collaboration, and being able to execute on that.. is unique as a partner.”
THE PROBLEM
Pocketnest wants to leverage AI to increase user engagement. They are looking for partners that can idealize the AI feature(s), leverage AI to bring value add, and to develop AI solutions in a condensed timeline. As a financial company, they are keen to avoid the common GenAI pitfalls such as providing incorrect answers to users.
CUSTOMER CASE STUDY 02: ZERO SHOT BOT
BCS Technology International Pty Ltd
THE PROBLEM
Zero Shot Bot is a startup aiming to create a chatbot platform that helps users build FAQ chatbots. Zero Shot Bot needs both AI expertise and backend expertise to develop and deploy this product idea.
CUSTOMER CASE STUDY 03: MYCA
THE PROBLEM
Founders plan to develop a AI-powered productivity tool for high-performing individuals to manage their tasks, habits and goals.
CUSTOMER CASE STUDY 04: TRUESELPH
Trueselph Inc
THE PROBLEM
Trueselph is a startup aiming to create a conversational AI platform that helps users build customized “Selphs”, the human-like AI with an avatar (face and voice) that can have a conversation with people. Trueselph does not have AI expertise to develop this product. They also have a short timeline to build out this product idea.
CUSTOMER CASE STUDY 05: TOBU
In these unique times where AI dominates discussions, Jaseci’s team strategically charted our path from the outset. Their approach not only resulted in patented AI solutions but also breathed life into our original vision"
THE PROBLEM
Founders had a concept that needed to be proven out before going to secure institutional investors with no in-house development team. The solution required a dynamic solution that could allow people to store and relive photos and memories in a intuitive and engaging manner.
Developed AI solutions for
Start-ups that Jaesci powers
Implementation partners - 1000+ developer network
Build you own GPT and beyond
Customers leverage Jaseci to build their own customized GPT, general conversational AI , AI assistant for training, HR support, etc, instant analytics and deep customer insights.
Chatbots
Digital Assistants
Search & Recommendation Systems
Facial Detection &
Recognition Systems
About
Jaseci was founded by Dr. Jason Mars, Computer Science professor at the University of Michigan. He leads a research lab specializing in artificial intelligence and large-scale computing. He is a pioneer in conversational AI (Wired article). He has founded multiple companies that have delivered AI solutions to over 20 million users across diverse sectors and companies (USbank, Barclays etc).
Jason Mars
Creator of
Jaseci
Author of
Breaking Bots
Professor of CS
Research Labs
Powered by cutting edge innovations and techincal solutions created in the University lab. Check out Jaseci Labs
Team
20 core advanced AI developers
5 Ph.D.s
+1000 developer through partnership
Patents and Papers
100 top tier papers in AI and systems
30+ AI patents
Awards
Technology leader for Articifial Intellgience - Frost & Sullivan
Gold Stevie “best new product/service of the year”
Crain Business’s 40 under 40
Bank Innovations Most Innovative CEO
CARAH Award, ISCA/MICRO/ASPLOS hall of fame, Google research award
Core team
Dr. Jason Mars
Professor at University of Michigan, Founder
Dr. Lingjia Tang
Professor at University of Michigan
Dr. Yiping Kang
Research Fellow at University of Michigan
Dr. Kris Flaunter
Professor at University of Michigan, advisor
Chris Clarke
AI Ph.D. resercher, University of Michigan
Dr. Logee Velmanickam
Professor at University of Moratuwa
Jayanaka Dantanarayana
AI Ph.D. researcher, University of Michigan
What industry leaders are saying about JaseciLabs...
A single step for AI,
A giant leap for mankind.
Every Developer
a Devops
Jaseci is an end-to-end open-source and Open
Computational Model, Technology Stack, and Methodology for bleeding edge AI. It enables developers to rapidly build robust products with sophisticated AI capabilities at scale.
01 Bleeding edge AI ready for use
- A wide range of bleeding edge AI models ready to use out of the box.
- Task-level AI models across language, vision, etc domains, engineered and configured by the top AI science so you can directly plug and play
02 Rapid backend development that requires ZERO backend knowledge
- Simple language features to grasp for front engineer developers to quickly prototype backend.
- Intuitive, novel programming paradigm that reduces lines of code by orders of magnitude, even for skilled backend developers
03 Automated API generation
- Automatically generates RESTful API endpoints and other SDK libraries interface based on your code.
- No more having to worry about the complexity of web service frameworks like Django or Flask, developers can focus their energy on building the best AI features.
04 Automated scalable deployment that requires ZERO devops knowledge
- Out-of-box production-grade containerization and orchestration so you can stand up a production-ready stack in minutes.
- Novel load balancing and facilitation techniques. Your production Jaseci cluster scales intelligently with your application’s demand
Mind. Machine. Magic
AI on Demand
Our mission is to make AI accessible to every developer. Jaseci is an end to-end open-source and Open Computational Model, Technology Stack, and Methodology for bleeding edge AI. It enables developers to rapidly build robust products with sophisticated AI capabilities at scale.
Bringing AI to the people
If you can use jQuery,
you can use Jaseci
Something here about how easy it is to create value, using our proprietary ‘glue’ language, that integrates will all major languages – Tensor flow, K8s etc (logos will be helpful)
Real Innovation. Quickly.
Don’t let something as mundane as the API get in the way of your creativity. The leaders of tomorrow are in an ever quickening race to bring real value to market and turn dreamers into realists.
Startups that are looking to build the next generation of AI products and want to go from idea to proof of concept in 2 weeks. They want to be able to prototype and test their idea on a daily basis without having to worry about backend development or devops. They want to be able to iterate over their idea as fast as they can code with a bleeding edge AI stack without having to worry about backend development.
Developers who want to quickly build and deploy a backend application with powerful AI. They want to be able to easily use AI models in all major programming languages. They want the ability to build their own AI models and plug them into their applications in all major programming languages. They want to be able to create a machine learning application that can be deployed on Google, Amazon or Azure with zero knowledge of cloud infrastructure.
Cost Efficiency
Development Speed
While the Jaseci Stack abstracts core infrastructural needs for deployment, scalability, data structures, etc., the Jaseci programming language provides syntactic sugar that allows the development of:
Scalable and easily maintainable codebases
Libraries to support core needs of developers working on AI models