AI request filtering
Bring security and compliance rules into connected AI workflows. The Ignituz AI Governance Plane evaluates requests before they reach the model, applying the controls configured for that workflow.
Explore this serviceAI Governance / Policies by team and use caseDifferent work.
Different work.
Different AI boundaries.
Customize governance rules to your organization’s internal standards and applicable industry standards. We translate those requirements into a scoped configuration, with rules reflecting the data and working practices of legal, medical, and development teams.
Who it is for
A practical starting point.
Security and compliance teams working with legal, medical, engineering, and business owners.
The challenge
A single broad rule can be too restrictive for one workflow and too permissive for another. Start with the purpose and information involved, then define the applicable policy.
Inside the engagement
What we work on together.
01
Legal workflows
Discuss client confidentiality, case information, and permitted AI use with the legal team. Identify the sensitive identifiers and request patterns that the selected controls should address.
02
Medical workflows
Identify how patient-related information enters the proposed workflow. Agree the intended use, sensitive-data handling, and review responsibilities with the relevant owners.
03
Development workflows
Define how credentials, internal information, and engineering context should be handled in connected coding assistants and development tools. Test the supported checks with representative examples.
04
Your standards, translated into rules
Map customer policies and applicable industry standards to supported request checks and handling rules. Agree expected outcomes, document coverage and gaps, and assign owners to review changes as requirements evolve.
Practical outputs
Make progress tangible.
We agree the scope and outputs around your starting point. A typical engagement can include:
- A policy matrix mapping customer and industry requirements to workflow rules
- Named policy owners and a change-review approach
- Configuration priorities for the governance plane
- Example requests for policy validation
In context
Example: a shared AI platform, separate needs
A legal team and a development team use the same AI platform for different work. Their owners agree distinct handling requirements, then validate the rules for each connected workflow against examples of permitted and restricted requests.
Getting started
Agree the next useful step.
Bring a priority workflow and the people who own it. We will review the intended outcome, dependencies, and constraints, then define an initial scope and acceptance criteria.
These are policy-design engagements, not claims of pre-certified sector packs or automatic legal compliance.
Plan this engagementExplore AI Governance
Go deeper into the services.
Monitoring and enforcement evidence
Make connected AI activity reviewable. Use request traces and policy outcomes from the governance plane to understand how configured controls behave in everyday work.
Explore this serviceGovernance rollout and operating model
Put autonomy with accountability into practice. Introduce the AI Governance Plane with a clear scope, accountable owners, and a path from the first connected workflow to broader adoption.
Explore this service