01
Bound the task
Define exactly what the agent can read, decide, and do.
SERVICE / 02
AI Agents
We design AI agents around a specific job, approved data, permitted tools, and clear escalation rules so intelligence becomes useful without becoming unpredictable.
Problems we help solve
What we deliver
- Agent task and boundary design
- Knowledge and retrieval setup
- Tool and workflow connections
- Evaluation scenarios
- Approval and fallback controls
- Activity logging
How we work
02
Evaluate
Test the agent on representative and difficult business examples.
03
Integrate
Connect approved actions with monitoring and human review where needed.
Frequently asked questions
Is an AI agent the same as a chatbot?
No. A chatbot is an interface; an agent may also retrieve information, use approved tools, and participate in a workflow.
Can it act without approval?
Only for low-risk actions that you explicitly approve. Higher-impact steps should remain human-reviewed.
How is quality measured?
We define task-specific evaluations for accuracy, completeness, safety, and successful escalation.
Relevant case studies
Connecting Grepin’s Community Operations with Automation
Slarivo structured Grepin’s member, gym, community-support, and content-operation workflows across its connected fitness ecosystem.
Automating APYVA’s Non-Clinical Care Coordination
Slarivo structured APYVA’s appointment, reminder, administrative follow-up, and support-routing workflows without automating clinical decisions.
Practical implementation guides
Human-in-the-Loop AI Automation: When Approval Is Essential
Human-in-the-loop automation gives AI a bounded role while a responsible person reviews uncertain, sensitive, or high-impact decisions. It is most useful when speed matters but the cost of a wrong action is too high for silent autonomy.
What's the Difference Between AI Automation and Traditional Automation?
Traditional automation follows explicit rules with predictable inputs. AI automation adds models that can interpret less-structured information, making it useful when emails, documents, language, or context vary from case to case.
How to Automate Customer Service with AI
AI can improve customer service by classifying requests, retrieving approved information, drafting responses, summarising history, and routing cases. The objective should be faster, more consistent support with clear human escalation.