Our latest post on why enterprises should invest in Custom AI Models . Click here.

A custom AI model trained on private data

Existing LLMs don't cover your knowledge domain? Train your own AI model which understands your business like no other.

A ChatGPT that works for your business only.
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Just like ChatGPT simplifies the world's knowledge

a custom model simplifies your company's know-how, making it everyone's go-to resource

Teaching LLMs new Knowledge Domains

Typically, LLMs are trained on publicly available knowledge, meaning they would be very good at generic tasks but suck at understanding your core business.
At Clio AI, we build a capable Llama 2 that understands your knowledge domain, your business, and can add value without excessive prompt engg or finetuning
Clio AI model schematic

"An average knowledge worker spends half a day just reading emails and searching for information"
- McKinsey

AI powered search and summarization can boost individual productivity by > 50%.
Less time searching for contextual information
Hours saved per employee every year

Make your competitive edge count

ChatGPT is very good at answering questions about the world. A custom model would be equally adept at answering questions about the business, more accessible to your employees and better at uncovering insights than the rest of the market

Efficient Knowledge Utilization

A Custom model pretrained on proprietary data extracts insights far better than any fine tuning or RAG application

Better Compliance and Governance

A Custom LLM will always stay within your data, compliance, and other policies without needing explicit instructions needed on public LLMs.

Enhance Decision Making

A Custom LLM becomes a reliable advisor by distilling complex information into actionable insights, facilitating informed decision-making across various business domains.
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Custom model is for companies with huge data sets

When you want to teach a model a pattern, basic finetuning is good (about 5k-50k tokens/words). When you have large datasets, better to build and train your own model

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Lots of proprietary data (> 1M tokens[1])

It's hard to finetune with such a large amount of data and existing models do not perform well.

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Domain Knowledge

Basic Finetuning would improve response styles but would suck if the model did not have any training related toknowledge domain.

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Compliance Needs

For high compliance requirements, a model has to be customized specifically and updated periodically.

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Multiple business apps and databases

Clio AI connects with 300+ apps and can set up continuous learning based on updates from each app.

Reports - Elements Webflow Library - BRIX Templates


When you need to control your system prompt and initial instructions according to business requirements.

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Data Protections

With granular permissions, Clio AI can ensure that every employee can answer questions from the info they have access to.

[1]: One token is about 4 characters. 1000 Tokens make up a page of 750 words.

Build your knowledge model right away

Supercharge your company's productivity by harnessing the massive reservoir of untapped data and insights.
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A digital brain for every company

Accessing the proprietary knowedge and institutional memory buried deep in files would teams get that jump in productivity as it works for ChatGPT and generic tasks like Marketing copy generation.

Cost Comparison - Open AI vs Llama 2

Saving Costs

With Open AI, they say training a model will cost $2M-$3M at the minimum. Plus compute costs.
With Clio AI, we pretrain an open source model and you can lower the costs by about 90%.

It takes about 2-3 months for a custom model to go live.

Highly Skilled Team

Clio AI's CTO has deployed Machine Learning Models at a similar scale at Tokopedia in his previous life.

We have experience in taking a instruction following LLAMA-2 from pretraining to a RLHF level (ChatGPT) that can continuously learn from human feedback.

Clio AI Compliance Solutions

High Control and Repeatablity

We understand what it takes to deploy a large scale model for enterprises.
You can set custom policies, control access, and do a number of other stuff depending on regulatory and compliance needs.

Harnessing Collective Knowledge

Morgan Stanley Wealth Management deployed their own model harnessing the knowledge and insights, housed across many internal sites, mainly in PDF format. They used GPT4 and OpenAI to do it. Some select quotes from the story. Full article here
“You essentially have the knowledge of the most knowledgeable person in Wealth Management—instantly. Think of it as having our Chief Investment Strategist, Chief Global Economist, Global Equities Strategist, and every other analyst around the globe on call for every advisor, every day. We believe that is a transformative capability for our company.”
Jeff McMillan, Head of Analytics, Data & Innovation
Morgan Stanley Wealth Management
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"Key to ensuring good client service is our ability to invest at scale in technology. (OpenAI) is empowering Morgan Stanley with the marriage of human advice and technology—something to which we are completely committed. This endeavor has been particularly rewarding. The buy-in and engagement across the organization has been impressive."
Jeff McMillan, Head of Analytics, Data & Innovation
Morgan Stanley Wealth Management
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"Today, more than 200 employees are querying the system on a daily basis and providing feedback. The focus will always be on getting advisors the insight they need, in the format they need, instantly. The effort will also further enrich the relationship between Morgan Stanley advisors and their clients by enabling them to assist more people more quickly."
Jeff McMillan
Morgan Stanley Wealth Management
company logo

Build your own custom model like Morgan Stanley

Clio AI enables you to harness the powers of your own business data, and build your own knowledge model, with lower resources and double quick time.
Get a demo to find out how.
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Save time, boost revenue, do more


less time on finding information


Hours saved per employee per year


Faster Decisions

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Gen AI tailored to your specific needs

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Frequently Asked Questions

Clio works with you every step of the way to enable free flow of knowledge across the organization.

Have more questions?

You can connect with us on email. Just send your queries to ankit@clioapp.ai and we would respond as quickly as possible.
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What is a custom model? Explain in simple terms

We build and train a Gen AI model like GPT 4 or Llama-2-chat. Instead of being trained on generic data, we train Llama-2 foundational model on your company data so that it accurately answers questions about your business without having to build RAG or finetuning mechanisms.

Okay, how does it work exactly?

Your company has three sources of data - employee interactions, reports/memos, and databases. We combine all of it, train a model pretaining with your data, build an RLHF pipeline and everything else to get you a best in class gen AI model that understands everything about your business.

Why can't I just finetune existing models?

Finetuning works when the data is small(~50K tokens) and you want to teach the model specific patterns. You cannot teach a model a new knowledge domain by using Finetuning no matter what the model is.

Why can't I just use Retrieval (RAG)?

RAG (Retrieval Augmented Generation) works when the context is small enough to fit inside a 8k token prompt. It's accuracy decreases with more and more data and would not work that well when the number of tokens are huge.

Can I deploy it on my own private cloud servers or premises?

Yes, we enable deployment on your own premises. This can further reduce the costs and ensure that your data and secrets literally do not leave your premises. You can just tell us your preferences while getting a demo if you would prefer a private cloud or on premise deployment.

How much is the pricing?

While Open AI starts at $2M-$3M minimum for this kind of thing, we would do it at a fraction of the cost. You can expect about 90% cost reduction using Clio AI rather than Open AI

Is the model trained only at the start?

No. While the model is trained once, and would need to be every few years, we also build a poweful Reinforcement Learning and Human Feedback Pipeline (RLHF) which can keep the model updated and gives out better answers based on previous human feedback.

Can I have a knowledge model for an individual/team as well along with whole org?

Clio AI is capable of training separate models for individuals and teams as well. We see the need and understand how some data has to be kept accessible to certain teams. We will be happy to assist you if you need this kind of tenancy.

Can it integrate with all my existing apps?

Yes, our output is an API endpoint which you can use to send data and receive responses. We provide a chat app on top of that. If you need to integrate specific apps, you can do so easily via the same endpoint.