MIKAKA AI builds AI agents and products on a multi-model architecture.
Our agents are model-agnostic: they work with leading LLMs, including xAI's Grok, and run on private local models where sensitive data demands it — grounded in your tools and data, with human review at each step.
Get in touchSee the productProducts and capabilities we are building on a multi-model foundation.
Our first product, MIKAKA Business Agent, researches options and drafts solution designs, technical proposals and reports — connected to your tools through MCP and tool use, with human review at each step.
See the product →A copilot for designing AI systems: clarifying requirements, comparing architectures and producing technical proposals.
Leading cloud LLMs, such as xAI's Grok, for advanced reasoning, combined with private local models for sensitive data that should stay on your own hardware.
Private workspace for clients (sign-in required) →From first idea to a dependable AI system in production.
We help you design AI solutions, choose the right models, plan architectures, review requirements and draft technical proposals.
Custom agents and integrations built on leading LLM APIs, including Grok — prompt design, tool use, MCP servers, evaluation and guardrails.
Run open models like DeepSeek and Qwen on DGX Spark, ASUS GX10 or Mac Studio for sensitive workloads — hardware sizing, deployment and tuning included.
Monitoring, model and prompt updates, and troubleshooting to keep your agents dependable.
Frontier capability where it helps, private control where it matters.
We match each task to a suitable model — a frontier cloud LLM such as Grok, or an open model running locally — and can switch models without rebuilding your agent.
Sensitive data can be routed to local models that never leave your network.
Mix cloud and local inference to balance cost, speed and capability for each task.
A short, clear path from first call to production.
Understand your workflows, data and constraints.
Choose the agent design, the models and the cloud/local split.
Build, evaluate and deploy the agent.
Keep it running, updated and improving.