Evaluate the actual workflow and controls rather than assuming custom software is automatically safer.
Both commercial and custom AI systems need appropriate sources, permissions, evaluation, and review. A custom system can be designed around a particular workflow, while commercial products may already provide useful controls and integrations. Retrieval does not eliminate inaccurate answers, and retention commitments must be verified for the chosen provider and contract.
- Test realistic questions, missing information, and inappropriate requests.
- Check permissions, provider terms, retention, and logging for the actual implementation.
- Require review for consequential actions and plan how failures will be handled.
| Capability | Custom system | Commercial tool | What to assess |
|---|---|---|---|
| Sources and answers | Retrieval and references can be tailored to approved sources | Knowledge connectors and references vary by product | Test accuracy, missing information, and whether citations support the answer. |
| Private data | Permissions, storage, and provider settings need deliberate implementation | Permissions, retention, and contract terms vary by product and plan | Verify the actual data flow and access boundaries. |
| Actions | Scoped integrations can support approved workflow actions | Tool and integration support depends on the product | Define authorization, review, audit records, and recovery. |
| Operating cost | Model usage, retrieval, hosting, evaluation, and maintenance | Licensing, usage charges, integration, and administration | Compare realistic usage and include ongoing support. |
| Human review | Escalation and review can be designed into the workflow | Review features and configuration vary | Test what happens when the system is uncertain or wrong. |
Grounding is useful, but it is not a guarantee
Retrieval makes relevant information available to a model. The system can still retrieve the wrong passage, miss important context, or produce an unsupported conclusion. Evaluation should include incomplete sources, conflicting information, and questions the assistant should decline or escalate.
Keep authorization outside the model
The application should enforce permissions before retrieval or tool execution. Define which actions are allowed, which require confirmation, and what gets recorded. An instruction in a prompt is not a substitute for an access check or a review step.
Compare the actual operating model
Estimate model usage, storage, retrieval, monitoring, evaluation, and support. A commercial tool may suffice for a standard task. A custom system may make sense when workflow fit or integration needs justify added engineering and maintenance.
Frequently asked questions
Does a custom AI agent eliminate hallucinations?
No. Sources, evaluation, clear uncertainty, and human review can reduce risk, but neither a custom implementation nor a commercial product guarantees correct answers.
Does custom AI automatically provide zero data retention?
No. Retention and training terms depend on the chosen provider, endpoint, settings, and agreement. Confirm those requirements before sending private information.
Ahmad Nadeem · CEO & Co-founder
Ahmad is an AI graduate from the University of Management and Technology. His work spans machine learning, computer vision, natural language processing, and software products. At Cortlinx, he leads the technical direction and turns business needs into practical product decisions.
Connect with Ahmad Nadeem on LinkedIn ↗