— Solutions
Contextual AI SolutionsFor Every Use Case
Custom retrieval-augmented generation systems designed for your specific domain, compliance requirements, and accuracy needs.
Enterprise Knowledge Base AI
The Problem
Teams waste hours searching through documentation, wikis, and internal systems. Critical information exists but isn't discoverable when needed.
Why Generic AI Fails
Generic chatbots lack access to your internal knowledge. Public AI services can't index your private documentation, and even if they could, security policies prevent uploading sensitive content.
How Contextual AI Fixes It
RAG ingests your entire knowledge base—Confluence, SharePoint, wikis, documentation—into a vector database. Semantic search retrieves relevant context, and the LLM generates answers grounded in your actual documentation with source citations.
Architecture
Customer Support Contextual AI
The Problem
Support teams struggle to find accurate answers quickly. Product documentation, FAQs, and troubleshooting guides are scattered across multiple systems.
Why Generic AI Fails
Traditional search returns irrelevant results. Support agents copy-paste from outdated docs. Customers wait longer, and resolution quality varies by agent experience.
How Contextual AI Fixes It
RAG unifies all support materials—product docs, ticket history, knowledge articles—into a single searchable system. Support agents query in natural language and receive accurate, cited answers. The system learns from feedback to improve retrieval over time.
Architecture
Legal / Compliance Document AI
The Problem
Legal teams need to find relevant clauses, precedents, and compliance requirements across thousands of contracts and regulatory documents.
Why Generic AI Fails
Keyword search misses semantic relationships. "Termination clause" won't find "early exit provision" even though they're equivalent. Manual review is slow and error-prone.
How Contextual AI Fixes It
RAG indexes all legal documents with semantic understanding. Queries like "What are the termination conditions?" retrieve relevant clauses regardless of exact wording. Every answer cites source documents for audit trails. Compliance officers can verify claims instantly.
Architecture
Internal SOP & Policy AI
The Problem
Employees can't find current policies and procedures. HR, IT, and operations maintain separate documentation that's often outdated or contradictory.
Why Generic AI Fails
Policy documents live in silos. Employees don't know where to look. When they find something, it might be outdated. No single source of truth exists.
How Contextual AI Fixes It
RAG creates a unified policy knowledge base. Employees ask questions in plain language: "What's the remote work policy?" The system retrieves current policies, highlights relevant sections, and provides citations. Version control ensures only current policies are retrieved.
Architecture
Sales Enablement AI
The Problem
Sales teams need product information, competitive intelligence, and pricing details instantly during customer conversations. Information is scattered across CRM, product docs, and internal wikis.
Why Generic AI Fails
Sales reps waste time searching for answers mid-call. Product information is outdated. Competitive intelligence isn't centralized. This slows deals and reduces win rates.
How Contextual AI Fixes It
RAG aggregates product specs, competitive analysis, pricing sheets, and case studies into a searchable system. Sales reps query during calls: "What are our advantages over Competitor X?" The system returns accurate, cited answers with source documents for follow-up.
Architecture
Healthcare / Clinical Notes AI
The Problem
Clinicians need to search patient histories, clinical guidelines, and research literature quickly. Information is buried in EHR systems and medical databases.
Why Generic AI Fails
EHR search is keyword-based and misses semantic relationships. Clinical guidelines are updated frequently. Research literature is vast and hard to navigate. Clinicians make decisions without full context.
How Contextual AI Fixes It
RAG indexes clinical notes, guidelines, and research papers with medical terminology understanding. Queries like "treatment options for condition X in patient with comorbidities Y" retrieve relevant guidelines and research. All answers cite sources for clinical validation. HIPAA-compliant deployment ensures patient data privacy.
Architecture
Website Visitor Intelligence
The Problem
Marketing and product teams see chat transcripts but miss the full picture. Most visitors browse without asking questions, so conversation logs alone cannot explain drop-offs, popular paths, or live demand on key pages.
Why Generic AI Fails
Generic analytics tools sit outside your AI stack. Chat-only metrics ignore navigation behavior. Stitching tools together adds cost, delays, and compliance overhead.
How Contextual AI Fixes It
Visitor Intelligence adds a lightweight tracker to your existing Contextual AI Systems workspace. Install one snippet per site, enforce domain allowlists, and view live visitors, journeys, history, and CSV exports alongside your RAG and widget tools.
Architecture
Need a Custom AI Solution?
Every use case has unique data, compliance, and accuracy requirements. Let's design a production-grade system for your organization.