The dais platform is an enterprise AI adoption accelerator designed to eliminate key roadblocks preventing organizations from scaling beyond proof-of-concept (PoC) to full production. Many enterprises struggle to operationalize AI due to compliance, data security, and access concerns—gaps that existing solutions, especially model-agnostic ones, fail to address. 

At dais, we are committed to solving this by providing a secure, scalable AI model orchestration platform enabling organizations to confidently deploy AI-driven workflows, particularly for agentic motions and retrieval-augmented generation (RAG) pipelines. Developers and data teams can quickly compose agentic workflows through an intuitive visual interface, seamlessly integrating large language models (LLMs), embedding models, filters, and data sources. 
 
Behind the scenes, dais automatically generates Agent Flow State Language (AFSL), a YAML-based format that enables smooth integration into existing DevOps pipelines. This dual approach—visual design and API-driven orchestration—reduces development time, streamlines production workflows, and ensures AI solutions can be deployed rapidly without sacrificing flexibility.
 
Our model-agnostic, end-to-end RAG pipeline allows enterprises to select and integrate the AI stack components that best fit their needs while addressing critical challenges in:
 
✔️ Prompt Engineering
✔️ Response Evaluation
✔️ Authorization
✔️ Security & Guardrails
✔️ Deployment & Monitoring
✔️ Ongoing Updates & A/B Rollout
✔️ AIBOM
✔️ AI Posture Management

AI/ML

Cyber Security

Enterprise Software

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Jason Kolb

Trebor Worthen

Chandler Sweetser

Matthew Ryklin

Jeff Smith

Jerald Dawkins

Courtney Carter

Skylar Wapato

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