Services/Enterprise Search

AI-Powered Enterprise Search

Retrieval that stays inside your tenant and respects access rights

Enterprise knowledge is trapped in silos: documents in SharePoint, conversations in Slack, procedures in Confluence, data in databases. Employees spend hours searching for information that already exists somewhere in the organisation.

S.AI.L deploys AI-powered enterprise search that understands context, respects access permissions, and never sends your data outside your cloud tenant. Semantic search finds answers, not just keywords.

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Compliance-first. Your cloud. No vendor lock-in. Principal-led.

35%

improvement in employee productivity for knowledge-intensive tasks with AI-powered enterprise search

McKinsey, 2024

50%

reduction in time spent searching for information when semantic search replaces keyword matching

Gartner, 2024

70%

reduction in duplicate work from undiscoverable existing content surfaced by intelligent retrieval

Deloitte, 2024

How it works

Four stages. One governed workflow.

From secure indexing to governance-ready retrieval — scroll through each stage to see how S.AI.L transforms your enterprise search

01

Stage 01

Tenant-Scoped Indexing

Index documents, emails, wikis, knowledge bases, and structured databases within your cloud tenant. No data leaves your availability zone. The indexing pipeline respects existing access permissions, data classification labels, and retention policies. Connectors integrate with SharePoint, Confluence, Google Workspace, Slack, and enterprise document management systems — all within your cloud boundary

What happens

  • 1Deploy indexing infrastructure within your cloud tenant (AWS, Azure, or GCP)
  • 2Configure secure connectors to document repositories, email, wikis, and databases
  • 3Preserve data classification labels and sensitivity markings throughout indexing
  • 4Implement incremental indexing for real-time content updates without full re-crawls

Outputs

  • Secure document indexing within your tenant
  • Multi-source connector framework
  • Data classification label preservation
  • Retention policy compliance
02

Stage 02

Access-Rights-Aware Retrieval

Every search query is filtered through your existing IAM and RBAC permissions. Users only see documents they are authorised to access — enforced at query time, not by obscurity. Role-based result filtering ensures that a marketing analyst cannot access board papers, and an external consultant cannot see client-restricted documents. Permission inheritance from source systems is maintained end-to-end

What happens

  • 1Integrate with your identity provider (Azure AD, Okta, Google Workspace IAM)
  • 2Map document-level permissions from source systems to search index
  • 3Enforce access controls at query time — not post-retrieval filtering
  • 4Log every search query and result set for access audit purposes

Outputs

  • IAM/RBAC-enforced result filtering
  • Permission inheritance from source systems
  • Role-based access control at query time
  • Access audit logging
03

Stage 03

Semantic Search & Contextual Answers

Retrieval-Augmented Generation (RAG) provides contextual answers from your corporate knowledge base — not generic web results or hallucinated model outputs. Every answer includes citations linked to source documents, enabling users to verify and drill down. Semantic understanding means searching for concepts, not just keywords: searching for 'supplier risk assessment process' finds relevant content even if those exact words are not used

What happens

  • 1Deploy embedding models within your cloud tenant for semantic indexing
  • 2Implement RAG pipeline: query → retrieve → generate answer → cite sources
  • 3Provide source document links and relevance scores with every answer
  • 4Support natural language queries across languages and technical domains

Outputs

  • RAG-powered contextual answers
  • Source document citations with links
  • Concept-level semantic matching
  • Multi-language query support
04

Stage 04

Governance & Audit Logging

Every query, result, access event, and user interaction is logged with timestamps and user identity. Full audit trail for compliance, information governance, and security investigations. Data classification labels are preserved throughout the search pipeline — sensitive documents retain their markings in search results. Usage analytics help information governance teams understand access patterns and identify over-permissioned content

What happens

  • 1Log every search query, result set, and document access with user identity and timestamp
  • 2Preserve data classification labels (confidential, restricted, public) in search results
  • 3Generate usage analytics: most-accessed content, search patterns, access anomalies
  • 4Provide information governance dashboards for compliance and security teams

Outputs

  • Complete query and access audit trails
  • Data classification preservation
  • Usage analytics and access pattern reporting
  • Information governance dashboards

Who this is for

Built for the leaders who own the outcome

Chief Information Officer

Unlock trapped knowledge across the enterprise while maintaining security boundaries and compliance with information governance policies

Chief Technology Officer

Deploy enterprise-grade search infrastructure on your own cloud — no data egress, no third-party indexing, no vendor lock-in

Chief Data Officer

Ensure data classification, access controls, and retention policies are enforced throughout the search pipeline with full audit trails

Ready to unlock your enterprise knowledge?

Speak to a Principal Consultant about deploying AI-powered search that stays inside your tenant, respects access rights, and provides auditable retrieval

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