Custom LLMs
AI that speaks your industry's language. Build and deploy custom Large Language Models around your use cases and business rules, with enterprise grade performance.
What are custom LLMs?
Custom Large Language Models (LLMs) are AI systems trained and fine tuned for your industry, domain, and business needs. They know your terminology, processes, and context, so their answers are more accurate and more relevant than a generic model's.
Blits.ai pairs foundation models with your proprietary data. The result is AI that speaks your language and understands your business better than any off the shelf model.
Domain specific training
Trained on your industry data, terminology, and business processes for higher accuracy
Data privacy & security
Your proprietary data stays inside your infrastructure, fully controlled and compliant
Continuous optimization
Models keep improving with new data and feedback, so you keep your competitive edge
Why teams choose Blits.ai for custom LLMs
Get more out of AI with models built around your business and the work you actually do
Higher accuracy
Train on your own domain data and use cases, so the model knows your terminology and handles your tasks more accurately than a generic model.
A lasting edge
Build AI capabilities your competitors cannot replicate, and hold a sustainable advantage in your market.
Lower API costs
Models sized for your tasks cost less to run than large general models. No more paying for processing you do not need.
Data sovereignty
Your sensitive data and AI models stay inside your infrastructure, under your complete control and fully compliant.
Faster response times
Run models close to your applications for shorter response times and a faster user experience.
Regulatory compliance
Train and deploy every model to your compliance requirements, and meet the regulations specific to your industry.
What matters before a custom LLM goes into production
A custom model is built from your own data and answers in your name. These are the questions risk, data and IT teams ask before they switch from a general model, and how Blits.ai answers them.
Regulations these use cases are mapped to in our AI Use Case Library
Rights to the training data, and control over it
Fine tuning starts with data you are allowed to use for training, such as documents and conversation logs that often hold personal data. Blits.ai cleans and labels that data inside the environment you choose, PII masking at the gateway keeps personal details out of prompts and logs, and both the data and the trained model stay under your control.
Tested against a general model first
A custom model has to earn its place on your own work. Before you switch, Blits.ai runs test suites built from your real conversations against the custom model and a general model, so you see how each one handles your examples. Because the platform is model agnostic, you keep the general model for any task where it does as well.
Model risk management and validation
Banks and insurers often bring a custom LLM under their model risk framework, with validation expectations such as SR 11-7 in the United States and PRA SS1/23 in the United Kingdom. Blits.ai gives your validation team test suite results, conversation logs and an audit trail to work from, and is ISO 27001, ISO 42001, SOC 2 Type II and PCI DSS Level 1 certified, GDPR compliant.
Where the model runs
Where a model runs decides where your data goes. Blits.ai deploys custom LLMs in our cloud in the EU, Qatar, Singapore, the UAE, the US or Australia, in your private cloud, or fully on premises, including air gapped environments. Running the model close to your applications keeps sensitive data inside your infrastructure and takes away the dependency on an external model API for that work.
Keeping the model current as your content changes
Prices and policies change more often than a model is retrained. Blits.ai grounds answers in approved knowledge bases, so a changed fact is updated there without waiting for a new training run, and the model is retrained on new data and feedback when terminology or tasks shift. Each new version runs through the test suites before it goes live.
Guardrails and monitoring around the model
A fine tuned model can still state something wrong with confidence. Blits.ai puts input and output guardrails around the custom LLM, answers only from approved knowledge, and refuses or hands over to a person with the conversation and context when a question falls outside it. Performance monitoring, analytics and conversation logs show how the model behaves after launch.
Built for the enterprise from day one
Enterprise AI expertise and a proven method take your custom LLM from raw data to production
Expert AI team
Our AI researchers and engineers have been building, fine tuning, and deploying large language models for enterprises since 2020, across many industries.
Fits your stack
Plug custom models into your existing applications, APIs, and business processes without disrupting the workflows you run today.
Proven methodology
A systematic approach to data preparation, model training, and deployment gives you consistent results and faster time to value.
Models that keep improving
New data, user feedback, and performance monitoring keep your models accurate and competitive long after launch.
Enterprise infrastructure
Deploy in the cloud, a private cloud, or on premises, with full control over data, models, and compute, and enterprise security throughout.
End to end support
From first assessment to ongoing maintenance, our team supports you across the entire model lifecycle. You never run it alone.
How we get you live
A proven four phase method takes your custom LLM from concept to production
Assessment & planning
Data analysis, use case definition, and technical architecture design
Data preparation
Data cleaning, labeling, and preparation for model training
Model training
Fine tuning, validation, and performance optimization
Deployment & monitoring
Production deployment, monitoring setup, and ongoing optimization
How we deliver it
You buy a working use case, not a license to build one. The Blits.ai team takes it from workshop to production and runs it for as long as it is live.
- 1
Workshop
Optional: one or two days to refine the use case, with its value and risk tier.
- 2
Demo
A working demo of your use case on the platform, before you commit.
- 3
Build and integrate
We build it on the platform and connect it to your systems and your own app.
- 4
Deploy
In our managed cloud, your private cloud, on premises or air gapped. Live in weeks.
- 5
Run and improve
Support, monitoring and model updates for as long as it is live.
Blits.ai is the enterprise AI platform and the team that delivers on it: we refine the use case with you in a workshop, build and integrate it with your systems and apps, deploy it in the cloud or on premises, and run and improve it for as long as it is live.
How we workYour use case, live in weeks.
Bring your data and your use case, and we build a model designed for your industry.
Frequently asked questions
The numbers behind the shift
Market context, with sources. The opportunity is real, and so is the risk of getting it wrong.