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info@extended-developments.comUseful applied AI
Agent Workflows
Agent workflows that plan and carry out defined tasks using approved tools, explicit state, checkpoints, and human escalation where needed.
Capability01 / 05
Designed around the job
What the work includes.
01
Task and decision-flow design
02
Agent state, tool, and approval orchestration
03
Logging, evaluation, and fallback behavior
Built for outcomes
The implementation is only useful when it improves the work around it. These are the outcomes we design toward.
Clear control over consequential actions
Traceable agent decisions and results
How we work
From intent to impact.
- 01
Choose a real job
We define the task, users, source material, actions, risk, and success criteria before selecting models.
- 02
Build the controlled loop
Retrieval, tools, state, permissions, approvals, and fallback behavior work together around the model.
- 03
Evaluate continuously
Representative test cases, production feedback, and monitoring make quality visible over time.
Also within AI Agents & Chatbots
Connected capabilities.
Good to know
Clear answers.
01Can an AI agent update our business systems?
Yes, when the relevant system exposes a suitable interface. We add narrow permissions, validation, logging, and human confirmation based on the risk of each action.
02How do you reduce incorrect AI answers?
We combine clear instructions, trusted retrieval, structured tools, constrained outputs, evaluations, and visible uncertainty. No single technique removes every error.
03Can we choose the AI model provider?
Usually, yes. We compare privacy, capability, latency, cost, hosting, and regional requirements before selecting a model setup.
Start a conversation
Ready to put Agent Workflows to work?
Tell us what needs to change. We will help define the right first step, the technical shape, and a realistic route to launch.