Don't just manage work. Deploy AI Agents that deliver it.
Kroolo AI Agents prioritize performance over simple conversation. They understand your specific business context to draft plans, route tasks, and automate high-quality deliverables directly inside your workspace.
Meet your new AI Team.
Use pre-built agents or build your own from scratch.
Hi Maya, I noticed your team is expanding…
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Problem · user stories · scope · added to board
A: From the comp policy, section 2…
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Role-based agents as listed on kroolo.com/ai/ai-agent. Example outputs are illustrative.
Outcomes first, then the work.
Each agent is built around a result your team cares about. Here is how three of them get it done, inside the tools you already use.
See cross-project risk before it becomes a delay.
The Project Agent reads every program, drafts structured outlines, flags risks that cut across projects and balances capacity across the portfolio.
Turn a prospect list into personal outreach, sent from your CRM.
The Sales Agent drafts personalised cold emails, sends them from your CRM, logs the calls and follows up until there is a reply.
Ask a question in plain language and get the answer, not a query.
The Data Agent writes and runs the SQL for you, then returns the insight in plain language so non-technical teams can self-serve.
Agents that speak your industry.
Examples are illustrative. Agents are configured for your processes and permissions.
From idea to working agent in five moves.
Design your perfect employee.
No code required. Just define the role, set the instructions, and choose their expertise.
From RFP to plan, hands-free.
Every run visible, every action owned.
Humans retain meaningful control over consequential decisions, with clear override paths. Every action has a named owner, an audit trail, and a chain of responsibility.
Skills, tools, harness, governance, evaluation. Configured once, governed always.
Every agent is set up in five layers, so it runs inside the guardrails you define and you can prove how it behaved.
Built for production, not for demos.
Most agent projects over-invest in prompts and under-invest in evaluation and tool design. Kroolo agents are designed around ten criteria that enterprise buyers can check.
- Clear success criteria and a "must not do" list
- Suggest only, act with approval, or act freely
- Defined per agent, not one agent for everything
- Cheaper models for extraction, stronger ones for planning
- Plans, acts, checks results, revises
- Stop conditions so runs never loop
- Read and write access set separately
- Errors the agent can act on, not stack traces
- Reusable connectors, including MCP
- Reusable procedures for repeat work
- Loaded on demand, so context stays lean
- Versioned, owned and reviewed
- Permission-aware retrieval from your data
- Short-term, long-term and task memory
- Compaction for long-running work
- Golden test set built from real tasks
- Trajectory checks, not only final answers
- Regression runs and live monitoring
- Human approval for payments, deletions and external sends
- Defences against prompt injection
- RBAC, audit logs, data residency, clear escalation
- Full trace of steps, tool calls and spend
- Cost budgets, timeouts, retries, fallbacks
- Scheduled and background runs
- Visible task list and actions
- Editable output, easy correction
- Questions only when a wrong guess is costly
- In the workspace, by API and by public link
- Chat tools your teams already use
- Open standards, including MCP
When one agent is not enough, they work as a team.
Chain agents into workflows. Each one hands its output to the next, and people approve the steps that matter.
FAQs on Kroolo AI Agents
More from Kroolo AI
- Agentic AI Development Services, Idea to ProductionKroolo's AI engineering team turns your problem statement into a governed, production AI product in 7 to 18 weeks, deployed in your cloud and run after launch.
- Enterprise AI Guardrails and Sovereign AI18 guardrail policies on every AI request, human approvals, a full audit log and deployment in your AWS, Azure, Google Cloud or data centre. See how it works.
- LLM Routing and AI Cost Control by TeamKroolo routes each AI request to a fast, balanced or frontier model, fails over when one is slow, and shows AI spend by team, workflow and agent. See it live.
- Enterprise AI StackSee how Kroolo's enterprise AI stack works: connectors, a knowledge graph with vector and keyword search, permission checks, agents and cited answers.
- Agentic AI Workflows, Governed and TracedCompose agents, skills, tools and human approvals on one canvas. Test with evaluations, ship with permissions and audit on, and trace every run.
- Context StudioDefine, test and govern the definitions, policies, playbooks and sources Kroolo AI uses. Versioned, permission-aware and shared by every agent.