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info@extended-developments.comUseful applied AI
Retrieval Systems
Retrieval systems that find relevant, permission-aware information and provide it to AI applications with citations and measurable quality.
Capability02 / 05
Designed around the job
What the work includes.
01
Content ingestion and indexing
02
Search, ranking, and access controls
03
Answer evaluation and source citation
Built for outcomes
The implementation is only useful when it improves the work around it. These are the outcomes we design toward.
Faster access to internal knowledge
Visible sources for user verification
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 Retrieval Systems 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.