Built for adaptability, our LLM-powered systems combine retrieval and generation to
automate complex workflows and deliver reliable, scalable intelligence.
While large language models (LLMs) like GPT-4 are powerful, out-of-the-box versions often fall short when applied to domain-specific tasks. They lack real-time access to proprietary or up-to-date information, risk hallucinations, and struggle with regulatory or contextual accuracy. Generic models can’t securely tap into your internal knowledge base, product documentation, customer records, or operational workflows. This creates a gap between what LLMs can do and what businesses actually need grounded, accurate, and customized outputs aligned with real-world use cases.
Whether you need an AI expert to augment your team or want a fully managed solution, we offer multiple ways to bring your custom LLM applications to life:
- Build with our talent through prompt engineers and LLM specialists who help craft, fine-tune, and scale your AI experiences
- Build with our support using our expertise in retrieval-augmented generation (RAG), vector databases, and domain-specific prompting
- Let us build for you custom LLM-based applications that combine reasoning, search, and contextual intelligence for real-world problem-solving
We specialize in building powerful generative AI systems that go beyond chat delivering tailored insights, automation, and decision support through large language models.
Offer personalized shopping assistants and customer service bots grounded in inventory, order history, and return policy data.
Offer personalized shopping assistants and customer service bots grounded in inventory, order history, and return policy data.
Power clinical assistants and research copilots that surface relevant protocols, case studies, and drug information from internal databases and journals.
Build product copilots that pull from support tickets, documentation, and codebases to assist users and developers in real time.
Develop AI tutors or curriculum assistants that serve up context-specific content from institutional resources, textbooks, and learning platforms.
Deploy intelligent assistants that analyze investment memos, compliance documents, and client portfolios for research and reporting tasks.