Kyndryl Teradata AI for Social Media Triage & Sentiment Analytics on AWS

Kyndryl Teradata AI for Social Media Triage and Sentiment Analytics on AWS modernizes customer care by unifying high-volume comment / DM triage, multilingual drafting, governed RAG, and real-time CX analytics. The solution reduces Time-to-First Response (TTFR), absorbs incident surges, and enforces policy and tone. This drives lower cost per interaction with full auditability across Facebook, X, Instagram, and TikTok.

How it works on AWS

Incoming social posts/direct messages are ingested into a React console and routed through a FastAPI + LangGraph pipeline on AWS. Amazon Comprehend detects language, sentiment, sarcasm, and custom entities (e.g., VIP/government mentions) for risk-aware prioritization. Retrieval fans out to enterprise knowledge and policies stored on Amazon S3, web sources, and Teradata Vantage search; Amazon ElastiCache for Redis accelerates repeat intents. Amazon Bedrock (via foundation models) drafts culturally appropriate, on-brand replies with citations. Agents approve in-console; escalations and formal responses are assembled and logged. Orchestration uses AWS Lambda and AWS Step Functions; APIs are exposed through Amazon API Gateway. Operations, security, and governance leverage AWS Identity Center (SSO), AWS IAM, AWS KMS, AWS Secrets Manager, AWS CloudTrail, and Amazon CloudWatch. Optionally, Amazon SQS, Amazon OpenSearch Service, and container hosting on Amazon ECS/EKS/Fargate support scale patterns. Amazon S3 stores prompts, drafts, approvals, and transcripts for immutable audit.

Intelligent analytics with Teradata

Teradata VantageCloud Lake serves as the governed analytics layer for TTFR, surge handling, quality/compliance scores, and closed-loop learning. Its Enterprise Vector Store powers similarity search and retrieval for RAG, while ClearScape-style analytics enable topic clustering, trend analysis, and KPI dashboards to continuously improve response quality and efficiency.

Key AWS services

• Engagement & orchestration: AWS Lambda, AWS Step Functions, Amazon API Gateway.
• GenAI & NLP: Amazon Bedrock, Amazon Comprehend, Amazon Translate, Amazon Textract (where attachments require OCR).
• Data, cache & search: Amazon S3, Amazon ElastiCache for Redis, Amazon DynamoDB.
• Security & governance: AWS Identity Center, AWS IAM, AWS KMS, AWS Secrets Manager, AWS CloudTrail, Amazon GuardDuty.
• Observability & cost: Amazon CloudWatch, AWS Cost Explorer.
• Compute/container options: Amazon EC2, Amazon ECS/EKS/Fargate. What buyers get
• Faster TTFR & lower cost per interaction: Multilingual auto-triage and Bedrock-generated drafts cut handling time and agent tab-switching.
• Quality & compliance at scale: Tone control, policy templates, VIP/government detection, and approval workflows improve consistency and auditability.
• Surge resilience: Queue prioritization and bulk actions help clear backlogs during incidents (e.g., flight delays, outages, recalls).
• Closed-loop CX analytics: Real-time dashboards, topic clustering, and feedback signals continuously tune models and playbooks.
• Enterprise-grade governance: Role-based access (AWS Identity Center), encryption (AWS KMS), secrets rotation, and complete artifacts in Amazon S3.

Typical flow

1. Post/DM appears in console with SLA timers;
2. Comprehend classifies intent, language, sentiment/sarcasm; custom entity checks flag VIP/government;
3. RAG retrieves from S3/web/Vantage; Redis serves hot snippets;
4. Bedrock drafts a grounded, on-brand reply; high-risk items require reviewer approval
5. Publish response; create escalation/email when needed;
6. Persist artifacts to S3; KPIs flow to VantageCloud Lake for dashboards and optimization;

Deployment & fit

Designed for airports/airlines, hospitality, public sector/utilities, retail/e-commerce, and FSI where multilingual, sentiment-sensitive engagement is critical. The AWS-native, serverless core minimizes ops overhead, while Teradata provides governed analytics and vector search for repeatability across regions and brands.

Expected outcomes: 60–80% TTFR reduction, 40–50% lower cost per interaction, ≥95% triage accuracy, >95% peak-hour surge absorption, and measurable improvements in public sentiment and policy compliance.