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AI Powered Dashboard - 15 Rock

Project overview

The client engaged us to design and ship production-ready AI development—not just a demo. The brief: turn fragmented data and manual workflows into intelligent features that improve speed, accuracy, and user experience.
We architected a secure, scalable stack including data pipelines, vector search/RAG, model serving, and MLOps (versioning, CI/CD, monitoring). We delivered two initial use cases—conversational search and automated triage—on a modular foundation that lets new models and features plug in without rewrites.

Project Solution

We rolled out a production-grade AI development program over 60 days, which included:

  • Data connectors & governance – secure ETL from CRM/Docs/Tickets with PII redaction and access controls.

  • Vector search & RAG – curated knowledge base, embedding pipelines, caching, and fallback retrieval.

  • Model orchestration & tools – prompt flows + function calling for classification, routing, and content generation.

  • Quality & guardrails – golden datasets, automated evals (precision/recall, hallucination checks), policy filters.

  • Deployment & UX – autoscaled APIs, CI/CD with canary releases, observability dashboards, and chat/assistant UI.

Our agile approach delivered incremental value without disrupting the existing product or brand experience.

In just 2 months, the client saw:

  • –32% average handling time on targeted workflows

  • +26% self-serve resolution/deflection via the AI assistant

  • 93% intent/answer accuracy on the golden test set

  • –38% manual effort for repetitive labeling and triage tasks

These outcomes established a stable AI foundation the team can extend with new use cases and models.

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Success Rate

Challenges & constraints

We faced several challenges common to service-based websites:

  • Limited labeled data and domain drift → addressed with weak supervision, synthetic data, and human-in-the-loop review.
  • Privacy & compliance (PII/GDPR/CCPA) → data minimization, encryption, redaction, role-based access.
  • Legacy systems & third-party APIs → resilient connectors, idempotent jobs, retries/queues.
  • Latency and cost targets for LLM inference → RAG with caching, batching, fallbacks, and prompt/tooling optimization.

Project Name

AI Powered Dashboard - 15 Rock

Category

AI/ML

Duration

2 Months

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