AI Product Development · 02
Generative AI.From experimentation to production.
Generative AI is changing how organizations create content, access knowledge, and automate work. Our generative AI consulting services help businesses move from experimentation to production.
We build solutions that leverage large language models and enterprise data in ways that are secure, scalable, and actually useful.
In short · Generative AI
- What it is
- Secure, scalable solutions on large language models and your enterprise data.
- Best for
- Teams moving generative AI from experimentation to production.
- You get
- Custom LLM applications, chatbots and RAG knowledge systems.
- After launch
- Guidance on governance, monitoring and enhancements.
How we work · 5 steps
How an engagement runs.
Opportunity Assessment
We identify where generative AI can create the greatest impact, focusing on use cases that align with business objectives and the data assets you already have. This is where our AI strategy consulting experience matters most.
Data & Knowledge Evaluation
Our team assesses data sources, documentation, and content repositories to determine how enterprise knowledge can be effectively put to work. Good artificial intelligence consulting services always start with what the data can actually support.
Solution Architecture Design
We design the full technical architecture: model selection, retrieval strategies, integrations, and governance requirements. Whether we’re building a custom LLM development solution from the ground up or integrating existing models into your stack, the architecture is designed to last.
Development & Validation
From custom LLM applications and chatbots to RAG-powered knowledge systems, we develop and validate every solution against both business and technical requirements. As a specialized generative AI consulting partner, we move fast without cutting corners on quality or security.
Deployment & Scaling
After successful testing, we deploy to production and provide clear guidance on governance, monitoring, and future enhancements. Our AI application development company experience means we’ve navigated these rollouts before, and we know where things tend to go wrong.
Partners
Built with the platforms your data runs on.
What generative AI solutions does Lineate build?
Custom LLM applications and chatbots, RAG-powered knowledge systems, and solutions that put enterprise data and knowledge to work in ways that are secure, scalable and actually useful.
How do you move generative AI from experiment to production?
Five steps: opportunity assessment, data and knowledge evaluation, solution architecture design, development and validation, and deployment and scaling with guidance on governance and monitoring.
What is RAG, and does Lineate build it?
Retrieval-augmented generation (RAG) connects a language model to your own documents and data so its answers are grounded in enterprise knowledge. Lineate builds RAG-powered knowledge systems as part of its generative AI work.
Can Lineate work with existing language models?
Yes. We build a custom LLM solution from the ground up or integrate existing models into your stack, with an architecture covering model selection, retrieval strategies, integrations and governance.
How do you handle security and quality in generative AI?
Every solution is validated against both business and technical requirements. We move fast without cutting corners on quality or security.
Got a project?
Let’s talk!
