dais Email Formats

Data Security Software Products • Tulsa, Oklahoma, United States • 11-20 Employees

dais Email Formats

dais uses 2 email formats. The most common is {first name}.{last name} (e.g., john.doe@dais.co), used 68.4% of the time.

Format	Example	Percentage
{first name}.{last name}	john.doe@dais.co	68.4%
{first initial}.{last name}	j.doe@dais.co	31.6%

Key Contacts at dais

Lucy Gonzalez

Marketing Director | Product, Brand, Gtm

Jerald Dawkins

Cio And Co-Founder

Company overview

Headquarters	Tulsa, Oklahoma, United States
Website	dais.co
Keywords	A/B Testing, Regulatory Compliance, Cyber Security, Compliance, Monitoring, Authorization, Data Security, Data Pipelines, Policy Enforcement, Rbac, Abac, Model Performance, Observability, Enterprise Ai, Ai Agents, Generative Ai, Ai Risk Mitigation, Rag Pipelines, Agentic Workflows, Ai-Driven Workflows, Ai Bill Of Materials, Ai Model Orchestration, Ai Posture Management, Policy Definition
Founded	2024
Employees	11-20

About dais

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