CogitX provides an integrated Agentic AI platform that combines generative AI, machine learning, and deterministic algorithms to create production‑grade AI agents fine‑tuned on a company’s own data and decision context. The platform offers composable components, policy‑driven orchestration, continuous evaluation, and a Governance Hub to ensure accuracy, cost efficiency, security, and regulatory compliance, with deployment options that include cloud, on‑tenant, on‑premise, or edge environments.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises face difficulty deploying AI agents that are accurate, secure, and compliant, often relying on fragmented tools that lack governance, incur hidden costs, and cannot be deployed on-premise or in regulated environments.
Solution
CogitX delivers an integrated Agentic AI platform that combines generative AI, machine learning, and deterministic algorithms to build production‑grade AI agents tailored to a company’s data and decision context. The platform provides composable building blocks for memory, reasoning, and tool integration, enabling agents to execute real enterprise workflows. Policy‑driven orchestration routes tasks across large and small language models, tools, and internal systems while optimizing for accuracy, cost, latency, and reliability. Built‑in evaluation continuously benchmarks agents for performance and behavior before release. A Governance Hub enforces access controls, guardrails, and audit trails, ensuring agents operate within defined boundaries. Deployment is flexible—on‑tenant, on‑premise, or at the edge—so organizations retain data sovereignty and meet regulatory requirements.
Target Audience
Primary customers are large enterprises across industries such as finance, insurance, manufacturing, and retail that need secure, governable AI agents for functions like marketing, sales, IT, customer service, HR, and finance.
Features
- Hybrid architecture that selects between generative AI, ML models, and deterministic algorithms for each task
- Composable agent components with memory, reasoning, tool use, and domain context fine‑tuned on proprietary data
- Policy‑based orchestration engine that balances accuracy, cost, latency, and reliability across LLMs and SLMs
- Continuous evaluation framework with task‑level benchmarks, simulations, and production feedback loops
- Governance Hub offering role‑based access, guardrails, and audit logging integrated at deployment time
- Flexible deployment options (cloud SaaS, on‑tenant, on‑premise, edge) with full data sovereignty and compliance controls
- Unified dashboard for managing, monitoring, and scaling multi‑agent workflows across the organization