Autonomous Agents
AI agents that think and adapt to complete complex tasks independently
Set up AI agents that figure out HOW to complete tasks - you just tell them WHAT you want done.
What It Does
Autonomous Agents think through complex problems and adapt their approach to reach the goal. Unlike workflows that follow predefined steps, agents decide what to do based on the situation. They can research information, use tools, make judgments, and adjust their strategy as they work. You provide the objective, and the agent figures out how to accomplish it.
Why It Matters
Many business tasks require flexible thinking, not rigid steps. Competitive research doesn't follow the same process every time - you need to adapt based on what you find. Customer support triage requires reading context and making judgment calls. Content generation needs creativity and adaptation to the topic.
Traditional automation fails at these tasks because they can't think. Autonomous Agents handle the judgment and adaptation, giving you true intelligent automation for complex work.
Business Impact
Tasks that require research, analysis, and adaptation can be automated without writing rigid step-by-step processes. An agent can research competitors, analyze offerings, identify gaps, and create comparison reports - adapting to whatever it finds rather than following a fixed script.
How It Works
Define the Goal
Tell the agent what you want accomplished (research these competitors and create a comparison report).
Agent Plans Approach
The agent thinks through how to achieve the goal (search for companies, visit websites, extract key information, analyze differences).
Agent Executes
Using available tools (web search, data extraction, analysis), the agent works through its plan.
Agent Adapts
If something doesn't work or new information changes the approach, the agent adjusts its strategy.
Delivers Result
Once the goal is achieved, the agent provides the completed work for your review.
Use Cases
Common Questions
How do I know the agent won't make mistakes?
Add approval gates at the end where you review the agent's work before it takes any action. Most customers use "AI does the work, human approves" pattern. You get 80 percent time savings by having AI do the research and drafting, while you spend 20 percent of the original time reviewing and approving rather than creating from scratch.
What tools can agents use?
Agents can use web search, access integrated systems (CRM, email, calendar, spreadsheets), query databases, and call APIs. During implementation, we configure which tools the agent can access based on your security and business requirements. You control what data and systems agents can interact with.
Can agents learn from feedback?
Yes, through two mechanisms. First, when you edit agent output before approving, we can use those edits to improve future executions. Second, you can provide explicit feedback ("focus more on pricing in competitor analysis"), and we incorporate that into the agent's instructions. The agent gets better at your specific use cases over time.
Knowledge Maps
Give AI agents a map of your business so they can navigate systems, understand context, and access the right capabilities when needed.
What Are Knowledge Maps?
Knowledge Maps give AI agents an understanding of your business landscape. Instead of loading every possible capability upfront, agents learn what knowledge exists (CRM, brand guidelines, policies, integrations) and access only what they need for each task. Think of it as giving the agent a directory of your business - they know what's available and can look up details when relevant.
Why Knowledge Maps Matter
Your business runs on siloed systems: sales data in one place, customer support in another, brand guidelines in documents, policies in wikis. Humans navigate this complexity because we know where information lives and when to look it up. Without organizational knowledge, AI agents either get overwhelmed with irrelevant information or lack access to what they need.
Knowledge Maps solve this by teaching agents to navigate your business the way an experienced employee would - knowing what knowledge exists and accessing it only when relevant.
Cost Reduction
An agent writing marketing content doesn't need access to your CRM tools or customer support integrations. But it DOES need your brand guidelines and messaging frameworks. Knowledge Maps ensure agents load only relevant context, reducing costs by 70-90 percent while improving response quality because the agent focuses on what matters for that specific task.
How Knowledge Maps Work
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Map Your Business - We identify key knowledge areas: CRM access, brand guidelines, integration tools, company policies, and other critical business systems.
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Agent Sees the Map - When an agent starts a task, it sees what knowledge is available but doesn't load anything yet - keeping the initial context lean and focused.
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Agent Navigates On-Demand - As the agent works, it loads only relevant knowledge. Writing content loads brand guidelines. Answering customer questions loads CRM and support documentation.
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Capabilities Expand - When knowledge loads, the agent gains both understanding AND tools. Loading "CRM knowledge" gives instructions on how to use it PLUS actual tools to query customer data.
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Context Persists Intelligently - Some knowledge stays loaded for the session (brand guidelines used throughout), while task-specific knowledge clears automatically (one-time CRM queries).
Last Updated: 2025-11-26