LightBot
Agentic Workflow Orchestration for High-Velocity Lead Conversion
Autonomous AI agents designed to automate complex multi-step workflows with zero-code orchestration.
Cognosys AI is a leading web-based autonomous agent platform designed to democratize complex task execution through advanced recursive decomposition. Built on a multi-model backbone, it allows users to define high-level objectives which the agent then deconstructs into logical sub-tasks, executing them sequentially while utilizing real-time web browsing, memory persistence, and tool integration. In the 2026 market landscape, Cognosys distinguishes itself by bridging the gap between raw LLM capabilities and practical enterprise utility. Its technical architecture focuses on 'agentic reasoning,' where it doesn't just predict text but validates its own outputs against defined goals. The platform has evolved into a sophisticated middleware that allows for the creation of 'persistent agents' capable of long-running operations across diverse environments. By abstracting the complexities of prompt engineering and loop management, Cognosys enables non-technical users to deploy agents that perform market research, code generation, and data extraction with minimal supervision, positioning it as a core component of the modern AI-augmented workforce.
Uses a hierarchy of prompts to break a single objective into a tree of sub-tasks, ensuring granular execution.
Agentic Workflow Orchestration for High-Velocity Lead Conversion
Build custom AI agents to automate your most repetitive operational workflows without writing a line of code.
The no-code foundry for deploying production-ready AI agents and multi-modal workflows.
The semantic knowledge fabric for high-velocity enterprise intelligence.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Automatically switches between high-reasoning and high-speed models based on task complexity.
Vector-based storage of previous task outputs for retrieval in future agent runs.
Agents can write and run Python scripts in an isolated environment to process data or perform calculations.
Multi-user environment where teams can view and interact with running agents in real-time.
Upload proprietary PDFs or documentation to ground the agent's knowledge base.
Cron-based triggering of agent workflows for recurring reports or monitoring.
Manual tracking of competitor pricing and feature updates is time-consuming and prone to gaps.
Registry Updated:2/7/2026
Agent generates a summary report and sends it via Webhook to Slack.
Recruiters spend hours finding candidates with niche skills across GitHub and LinkedIn.
Processing thousands of reviews across different platforms to find actionable feedback.