Generative AI Development Company for Custom GenAI Products

It builds applications on large language models and other generative models, such as chat and search over company data, content and document tools, assistants, and agents, along with the integration, evaluation, and deployment work needed to run them in production.

Internal knowledge assistants, customer-facing chatbots, document analysis and summarization, content generation tools, AI copilots inside your product, and agents that complete multi-step tasks.

Usually not. Most projects start with a pre-trained model plus retrieval over your existing documents. Fine-tuning needs a curated set of high-quality examples and is worth it when you need consistent behavior or format. See RAG vs fine-tuning.

Most products use both: a hosted or open-weight model, plus custom code for retrieval, integrations, guardrails, and the user interface. A fully custom model is rarely needed. When data cannot leave your environment, open-weight models can run on private infrastructure.

Timelines typically range from 3 to 10 weeks, depending on complexity, integrations, and whether fine-tuning is involved.

It can be, with the right design: access controls on what the model can retrieve, model providers whose terms do not allow training on your data, input and output filtering, activity logging, and private deployment where required.

Yes. We connect generative AI features to your CRM, SaaS product, website, or internal tools through APIs, SDKs, or custom interfaces.

We test outputs against evaluation sets, check for hallucinations and prompt injection, ground answers in your data with retrieval, and keep a human review step where errors are costly.