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OpenText Decision Service is well suited for centralized, rule-based decision automation, while Gemini can be used as an AI layer to interpret unstructured inputs, generate recommendations, and support human decision-making. Together, they can improve speed, consistency, and scalability across operational workflows.
Data flow: Gemini to OpenText Decision Service
Gemini analyzes incoming customer emails, chat transcripts, or case notes to identify intent, urgency, sentiment, and key entities such as product, region, or contract type. It then passes structured attributes to OpenText Decision Service, which applies business rules to determine the correct case priority, routing queue, SLA, or escalation path.
Data flow: Gemini to OpenText Decision Service
Gemini extracts relevant information from application documents, supporting statements, or uploaded forms, then normalizes the data for decision rules. OpenText Decision Service evaluates the extracted attributes against eligibility criteria, policy thresholds, and exception rules to produce an approve, reject, or refer outcome.
Data flow: Gemini to OpenText Decision Service
Gemini reviews free-text claim descriptions, incident reports, or supporting attachments to classify the request type and identify missing information. OpenText Decision Service then applies routing and validation rules to send the case to the right team, request additional evidence, or trigger a fast-track path for low-risk cases.
Data flow: OpenText Decision Service to Gemini and back
When a case falls outside standard rules, OpenText Decision Service flags it for exception handling and sends the rule outcome, supporting facts, and decision context to Gemini. Gemini generates a concise summary for reviewers, highlights the reason for exception, and suggests additional information needed before a final decision is made.
Data flow: Bi-directional
Gemini analyzes customer interaction history, notes, and current conversation context to infer intent and likely needs. OpenText Decision Service applies business rules to determine which offer, retention action, or service recommendation is allowed based on policy, customer segment, and risk profile. The approved action is then returned to Gemini for natural-language presentation to the user or agent.
Data flow: OpenText Decision Service to Gemini
OpenText Decision Service produces the formal decision outcome and rule trace for regulated processes such as lending, insurance, or procurement approvals. Gemini converts the technical rule output into a clear business explanation for internal users or customers, helping teams understand why a decision was made and what can be done next.
Data flow: Gemini to OpenText Decision Service
Business analysts use Gemini to summarize policy documents, regulatory updates, or process changes and identify which decision rules may be impacted. The updated rule requirements are then implemented in OpenText Decision Service, allowing teams to adjust decision logic more quickly without embedding changes in application code.
These integration patterns are especially valuable in environments where decisions must be both fast and explainable, and where unstructured information needs to be converted into structured inputs for deterministic business rules.