Create intelligent agents that reason, plan, and execute complex tasks across your entire tech stack. No PhD required.
Build agents that can think, reason, and act autonomously while staying within the boundaries you define.
Agents understand complex goals and break them down into actionable steps automatically.
Connect agents to any API, database, or service. They autonomously decide when and how to use tools.
Agents can retry failed actions, adapt strategies, and learn from outcomes in real time.
Interact with agents using natural language. No complex configurations needed.
Safety controls, approval workflows, and governance to keep agents within bounds.
Every agent action is logged. See exactly what decisions were made and why.
Lither agents combine large language models with tool access and memory to perform complex, multi-step tasks autonomously. You go from idea to a deployed agent in four steps.
From customer support to DevOps, AI agents automate complex workflows across every department. A few of the most common patterns teams ship on Lither:
Use any LLM provider. Switch models per agent based on cost, speed, or capability requirements, without rewriting your workflow. Lither stays provider-agnostic so you are never locked in.
Every agent follows the same clear loop. A user request or trigger arrives over chat, API, webhook, or schedule. The LLM brain reasons and plans, the tool executor makes the API calls and takes actions, and memory holds the context and history. Connected services like databases, CRMs, Slack, and email do the real work.
An AI agent combines a large language model with tool access and memory to carry out complex, multi-step tasks autonomously. You define a goal in natural language, the agent reasons about it, plans the steps, and uses the tools you grant to get the work done.
Lither is provider-agnostic. You can use leading hosted providers, run local or self-hosted models for privacy-sensitive workloads, or connect any OpenAI-compatible API as a custom provider. You can also pick a different model per agent based on cost, speed, or capability.
Every agent runs with built-in guardrails: configurable safety limits such as a maximum number of iterations, approval workflows that pause sensitive actions for a human to review, and governance rules. Every action is written to a full audit trail so you can see exactly what was done and why.
Agents can be triggered four ways: through a chat interface, via an API call, from a webhook, or on a schedule. The same agent can be reachable across all of them, so you can wire it into whichever workflow fits.
Agents can connect to any API, database, or service. Common integrations include knowledge bases, CRMs, ticketing systems, Slack, and email, and they autonomously decide when and how to use each tool to accomplish the goal.
Join the teams building intelligent automation with Lither AI Agents. Start free, scale as you grow.