Embedded Files
AI for fintech and trading
AI for fintech and trading
We work with financial companies — crypto, fintech and trading desks — building AI for market analysis, signals, risk and research with the security, auditability, and reliability that finance demands.
Large language models put to work
Large language models put to work
Large language models turn your text, documents and data into knowledge: they answer questions, summarize and reason. We help you choose the right model (open or commercial), integrate it and shape it around your use case. This is the foundation for everything below.
Build AI on your own data
Build AI on your own data
We connect your documents, wikis and databases to a model using retrieval-augmented generation (RAG), so your team and customers get accurate, up-to-date answers, each traceable to its source.
Tailor models to your domain
Tailor models to your domain
We fine-tune models on your data, terminology and tone (using parameter-efficient LoRA adapters) for sharper results on your specific tasks without the cost of training from scratch.
Automate workflows with AI agents
Automate workflows with AI agents
We build AI agents that reason and take action across your tools, APIs and systems, completing multi-step processes end to end, with guardrails that keep them safe, predictable and on task.
Keep your AI reliable and measurable
Keep your AI reliable and measurable
We add tracing, automated evaluation and dashboards for quality, latency and cost, so you can see exactly how your AI performs and catch problems before your users do.
Take your AI from prototype to production
Take your AI from prototype to production
We integrate, deploy and maintain your AI system in production, with monitoring, versioning, security and continuous improvement as your traffic and needs grow.
The right mix of AI technologies
The right mix of AI technologies
A production stack we know end to end: Spring AI for enterprise integration with your Java/Spring backend, LangChain for orchestration and agents, Ollama to run open models in your own environment, Milvus as the vector database for retrieval, and Langfuse for tracing, evaluation and analytics. We integrate Python-based AI stacks as well.
We consult on projects, mentor teams, lead by example, and design and implement AI-based systems.
We consult on projects, mentor teams, lead by example, and design and implement AI-based systems.
Page updated
Google Sites
Report abuse