Trusted Knowledge Foundation

The success of the platform depended on the quality of the information available to it. DataTheta therefore treated knowledge preparation as a central implementation activity rather than a simple content-cleaning exercise.

The team reviewed documentation, identified duplicate and outdated guidance, assigned owners, and created common metadata for product modules, software versions, integrations, and issue categories.

The Knowledge Foundation Included

• A unified taxonomy for products, modules, versions, and issue types.
• Clear ownership for important support documents and runbooks.
• Effective dates and version labels for release-dependent guidance.
• Retirement rules for outdated or duplicate information.
• Role-based controls for public, internal, and restricted content.
• Metadata for geography, subscription, entitlement, and configuration.
• Priority rules that favored approved instructions over informal comments.
• Feedback options for agents to flag inaccurate or unclear sources.

This process improved more than GenAI retrieval. It helped the company identify areas where important operational knowledge lacked ownership or depended heavily on individual employees.

Governance and Safety

Governance controls were built into the initial solution. The company wanted faster resolution, but not at the cost of security, customer commitments, or operational accountability.

Every AI-assisted answer required supporting evidence. Low-confidence results triggered clarification or escalation instead of producing an unsupported response.

Core Governance Controls

• Approved evidence required for every recommendation.
• Confidence thresholds for review and escalation.
• Permission controls based on the support agent’s role.
• Context filters prevent guidance from the wrong product version.
• Masking of personal information not required for resolution.
• Full logging of sources, generated text, edits, and outcomes.
• Human approval for financial and access-related actions.
• Specialist review for security and privacy-sensitive cases.

The system could not autonomously issue refunds, change subscriptions, modify user access, override policies, or make contractual commitments. These activities remained outside the approved automation boundary.

Implementation Approach

The platform was introduced through a controlled 12-week program. The first release focused on 12 high-volume support intents where knowledge was available and the business impact could be measured clearly.

During the first phase, DataTheta audited information sources, documented existing workflows, defined the taxonomy, and established baseline performance metrics.