Yevai

Our systems have been retasked to assist with the Palisades and Eaton fires. You may experience elevated response times.

Who we are:

We're a research, architecture, and applied AI implementation company focused on the ethical and equitable deployment of safe and reliable AI.

What we do:

We provide stable UIs, Integrations and APIs with performance comparable to a team of Data Scientists, Data Engineers, and Applied ML Engineers.

Features:

The strengths of frontier and fine-tuned models in one API.

Intuitive UI for non-technical users to perform big data analysis.

Scheduled actions, web watchers, and task-specific endpoints.

Real-time data from the web, APIs, documents, and databases.

Automatically prevent and fix hallucinations with arbiter models.

Low barrier to adoption with integrations like Slack, Outlook, etc.

Avoid sunk costs of vendor lock-in amidst a volatile AI landscape.

Zero maintenance: we provide stable APIs and handle the rest.

Same-week updates: you're always using the latest and greatest.

Deterministic and integration-friendly output from complex tasks.

Integrate with your data pipeline or have us set one up for you.

Continuous learning with model and embedding drift detection.

Frontier research and optimizations implemented every quarter.

Architecture:

Orchestrator

Our foundational model breaks complex tasks down, choosing the best runtimes and supervising execution, including falling back to a different vendor if one fails.

Runtime

An external or internal model for 0-shot or knowledge graph execution, with temperature, stop sequences, frequency, and presence penalties, plus specific context and tooling.

Context

Relevant data is presented in an optimal format for frontier models and our fine-tuned models, whether that's our secret sauce, a RAG context, or pre-/post-/re-prompting.

Tooling

A dynamically selected, properly limited scope of tools, queries, and APIs is exposed to a runtime during each knowledge graph traversal or completion.