Enterprise Intelligence Through Data & AI

Enterprise support teams overwhelmed by complex technical queries across thousands of product documents, with slow resolution times and inconsistent answers.

Built a hybrid RAG + GraphRAG architecture combining vector similarity search with knowledge graph traversal. Multimodal AI processes text, diagrams, and code snippets simultaneously.

60% faster ticket resolution, 85% accuracy on first response, reduced escalation rate by 40%. Handles 500+ queries/day across 12,000+ technical documents.

Documentation drifting out of sync with code changes, causing developer confusion and onboarding delays. Manual review couldn't keep up with rapid release cycles.

Gemini LLM analyzes code ASTs and cross-references documentation. Integrated into GitHub CI/CD pipeline with SonarQube quality gates. Auto-flags stale docs on every PR.

Eliminated 95% of doc-code drift. Reduced onboarding time by 30%. Runs automatically on every commit with zero developer overhead.

Generic LLM chatbots hallucinating answers about company-specific policies and procedures. Employees couldn't trust AI responses without manual verification.

RAG pipeline with Azure Cognitive Search indexes internal knowledge base. Every response includes source citations. Confidence scoring filters low-quality answers before delivery.

Hallucination rate dropped from 23% to under 3%. Source attribution on 100% of responses. 4x increase in employee trust and adoption of AI assistant.

Data siloed across 15+ systems with no unified view. Manual reporting took weeks, decisions were based on stale data, and no data governance framework existed.

Informatica ETL pipelines on AWS feeding a Snowflake data warehouse. PowerBI and Domo dashboards for real-time analytics. Alation for data catalog and governance.

Unified 15+ data sources into single analytics platform. Reporting time reduced from weeks to minutes. Full data lineage and governance compliance achieved.

Manual security assessments taking weeks per evaluation, inconsistent scoring across analysts, and no continuous monitoring capability for evolving threat landscapes.

NLP processes security questionnaires and compliance documents. ML models score risk posture automatically. Langchain powers conversational interface for security teams to query findings.

Assessment time reduced from 3 weeks to 2 days. Consistent scoring across all evaluations. Real-time threat dashboard with conversational querying for security teams.

Manually writing professional profiles for 80+ consultants, each requiring hours of drafting and editing. Inconsistent tone and branding across the team.

LLM with carefully engineered prompts and few-shot examples from approved profiles. Generates on-brand, accurate professional summaries from structured input data.

80% reduction in writing time per profile. Consistent brand voice across all profiles. From 3 hours per profile to under 30 minutes including review.

Thousands of procurement opportunities published daily across multiple platforms. Manual review missed relevant bids and couldn't scale with business growth.

RAG-based semantic matching against company capability profiles. Zero-shot classification categorizes opportunities by domain. NLTK extracts key requirements and deadlines automatically.

Processes 2,000+ opportunities daily with 92% relevance accuracy. Bid response time reduced by 65%. Discovered 3x more qualified opportunities than manual review.

Traditional IVR with rigid menu trees causing 40% call abandonment. Customers frustrated by "press 1 for..." navigation that couldn't understand natural requests.

Azure Bot Framework with Speech Services for natural language IVR. LLM understands caller intent in free speech. Conversation analytics track satisfaction and optimize routing.

Call abandonment dropped from 40% to 12%. Average handle time reduced by 35%. Customer satisfaction scores increased 28% after deployment.

Network administrators spending hours diagnosing issues by manually searching runbooks and documentation. Knowledge siloed in individual team members' heads.

Generative AI assistant with RAG over network runbooks and incident history. Adaptive learning improves from every resolved ticket. Secure CI/CD pipeline with Snyk vulnerability scanning.

Mean time to diagnose reduced by 55%. Knowledge retention no longer dependent on individual admins. Secure deployment pipeline with zero critical vulnerabilities.