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@Thinkata

Thinkata Intelligence

🧠 Thinkata

Building the next layer of intelligence
Thinkata creates modular, open components for agentic systems, retrieval-augmented reasoning, and knowledge-centric workflows. The goal is to help teams design AI that can think with their data, coordinate tools, and operate with predictable structure.

Our work includes

  • Agent orchestration primitives such as plans, loops, controllers, evaluators
  • RAG and data-awareness frameworks for multi-source reasoning
  • Knowledge interfaces that help systems use domain context reliably
  • Architecture patterns for scalable, production ready AI systems
  • Educational and strategic content for engineers and decision makers exploring the AI native transformation

🧭 How to Engage

  • Explore open repos, patterns, and active experiments
  • Follow @willmark for architecture notes, agentic design patterns, and AI native strategy
  • Collaborations, advisory, and pilot programs coming soon at thinkata.ai/contact

🪪 License

MIT License © 2025 Thinkata

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  1. promptlifter promptlifter Public

    Extend LLM queries with RAG (search + vector) in parallel subtask execution steps to produce long context output.

    Python 1

  2. conversations conversations Public

    Flexible OpenAI API compatible endpoint LLM conversations

    Vue

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