Large Language Models are powerful, but out of the box they don’t know your business. We build applied AI solutions that combine LLMs with your own documents, databases, APIs and visual data, so the system actually answers questions and takes actions that matter in your domain. That can mean RAG search across thousands of reports, automatic drafting of progress summaries from site photos, or copilots that help your team navigate complex workflows.
We work with a mix of commercial and open-source models: OpenAI, Anthropic, Google, as well as Llama, Mistral and other OSS models served via libraries like Hugging Face Transformers, vLLM or text-generation-inference. For retrieval and orchestration we typically use tools such as LangChain, LlamaIndex, vector databases (Pinecone, Qdrant, Weaviate, pgvector), and classic full-text search (Elasticsearch, OpenSearch). When multimodal is needed, we plug in vision-language models (VLMs) that can reason over text + images or text + 3D metadata.
Each solution is treated as a product, not a one-off script. We define prompts and tools, implement guardrails, evaluation and monitoring, and integrate the AI layer into your existing systems through REST/GraphQL APIs, chat interfaces, browser extensions or internal web apps. The outcome is a reliable assistant that your team can trust – with clear boundaries, logging and control over data privacy.