ENIGMA engineers Retrieval-Augmented Generation systems that connect AI with approved policies, SOPs, manuals, product data, proposals, support records and internal systems—so answers are relevant, permission-aware, traceable and supported by sources.
Approved Sources
Documents, portals, databases, APIs and controlled repositories.
Grounded Retrieval
Relevant knowledge is retrieved before the answer is generated.
Permissions & Citations
Users see authorized information with verifiable source references.
Built with access control, document ownership, version awareness, answer citations, confidence handling, audit visibility and human escalation—not unrestricted access to every company file.
Enterprise Knowledge Orchestration
Permission-Aware Answer Pipeline
Operations Manager · Verified Role
What is the approved process when a field installation fails quality inspection?
SOP
Quality Rework Process
Version 4.2 · Approved
Policy
Escalation Matrix
Operations · Current
Checklist
Site Closure Checklist
Field Team · Active
System Record
Project Status Rules
ERP API · Live
Grounded Answer
Mark the inspection as Rework Required, assign the designated project owner, attach the failed checklist, create a corrective task with the policy deadline and escalate repeated failures to the regional operations manager. Do not close the project until the re-inspection is approved.
The goal is not to make an AI sound confident. The goal is to make the answer useful, current, authorized and verifiable inside a real business environment.
Generic AI Assistant
closeMay rely on outdated or general information.
closeCannot reliably prove where the answer came from.
closeMay ignore department and document permissions.
closeKnowledge updates depend on changing prompts or retraining.
ENIGMA RAG Knowledge System
check_circleSearches current, governed knowledge sources.
check_circleReturns citations for verification and trust.
check_circleApplies role, department and document permissions.
check_circleRe-indexes approved updates without rebuilding the whole model.
The problem is rarely a complete absence of information. It is fragmentation across folders, emails, portals, databases and people—without a governed retrieval layer.
Policies, manuals, proposals and technical documents live across drives, chats, emails and personal folders.
Outcome: One searchable knowledge layer
Experienced employees answer the same policy, product and process questions throughout the day.
Outcome: Faster self-service with escalation
Teams unknowingly rely on old versions because ownership, approval status and expiry are unclear.
Outcome: Version-aware retrieval
A single assistant should not expose every contract, HR policy, customer record or internal document to every user.
Outcome: Permission-aware answers
New employees depend on colleagues to explain procedures, systems and exceptions that already exist in documents.
Outcome: Contextual learning inside work
Operational understanding remains undocumented or inaccessible when key employees change roles or leave.
Outcome: Institutional knowledge continuity
A production RAG system requires content pipelines, indexing, semantic retrieval, access control, answer generation, citations, monitoring and knowledge operations to work as one architecture.
01 · Sources
Files, portals, databases, CRM, ERP, APIs and approved repositories.
02 · Ingestion
Extract content, metadata, ownership, versions and access labels.
03 · Knowledge Index
Chunking, embeddings, vector index and structured retrieval.
04 · Governance
Role filters, document scope, freshness, confidence and escalation rules.
05 · Answer Layer
Generate an answer from retrieved evidence with citations and limitations.
06 · Experience
Web, mobile, portals, WhatsApp, CRM, support and usage monitoring.
Natural-language question from an approved channel.
Role, department and access scope are resolved.
Relevant authorized passages are selected.
Freshness, relevance and source authority are evaluated.
The model responds using retrieved evidence and rules.
Sources are shown, or uncertainty routes to a person.
The assistant experience, accessible sources and permitted actions can change according to the employee, customer, dealer or partner using it.
Answers can be grounded in HR policies, department SOPs, system guides, forms, onboarding documents and operational instructions while respecting employee access.
Policy and process questions
Explain approved procedures and link the original source.
Role-specific onboarding
Guide new employees through tools, responsibilities and checklists.
Human escalation
Route sensitive or unresolved questions to the correct owner.
Retrieve troubleshooting guides, warranty rules, order policies, service procedures and known resolutions while capturing unresolved knowledge gaps.
Agent-assist during tickets
Surface relevant steps and sources without searching multiple portals.
Customer self-service
Answer eligible questions on web, app or WhatsApp.
Retrieve product capabilities, qualification criteria, case-study material, proposal clauses and current commercial documents without inventing unsupported commitments.
Proposal research
Find relevant approved content for opportunities and industries.
Commercial guardrails
Surface exclusions, approval requirements and current terms.
Teams can ask about quality checks, escalation, dispatch, field execution, inventory rules and exception handling without relying on memory.
Step-by-step SOP guidance
Return the applicable process for a role and situation.
Exception identification
Highlight when the standard procedure is insufficient and escalation is required.
Connect manuals, specifications, architecture documents, release notes and troubleshooting knowledge for engineering, service and implementation teams.
Cross-document retrieval
Combine relevant evidence across multiple technical sources.
Version-aware responses
Prefer current product, software or equipment versions.
Retrieve approved clauses, controls, responsibilities and evidence while clearly showing source documents and escalation boundaries.
Clause-level citations
Link the response to the relevant section for verification.
Clear non-answer conditions
Escalate ambiguity, exceptions and decisions requiring authorized review.
The right approach may index existing sources, synchronize selected content or connect live business data through secure APIs.
PDF, Word, PowerPoint, spreadsheets, manuals and policies.
Approved drives, document libraries and knowledge portals.
Structured records, catalogues, tickets and operational data.
Customer, product, project and business-system context.
Retrieve current status and controlled application data.
Web, mobile, portals, WhatsApp, support tools and internal apps.
The system must know which sources are approved, who may retrieve them, how freshness is handled, and what happens when evidence is weak or conflicting.
Apply user, department, customer, dealer, project or document-level access before content reaches the model.
Prefer approved, current and authoritative knowledge over drafts or expired material.
Show which documents and passages supported the answer for verification and review.
Avoid unsupported answers when retrieval is weak, conflicting or outside the agent’s responsibility.
Resolve identity, organization, role, department and business context.
Filter by permission, approval status, version, date and knowledge domain.
Evaluate relevance, consistency and answerability before responding.
Route policy exceptions, sensitive decisions, conflicts and missing knowledge.
Documents change. Policies expire. Products evolve. Knowledge owners need a controlled process for approval, synchronization and review.
Identify who approves, updates and retires each knowledge domain.
Parse content, attach metadata, permissions, versions and source authority.
Re-index on schedule, event or controlled publishing workflow.
Use search and answer gaps to improve documentation and coverage.
Remove expired content and validate retrieval quality over time.
This scenario demonstrates the operating pattern, not a fabricated client result.
Question
“A project failed quality inspection twice. What should happen next?”
Identity & Context
Regional operations manager · Project ID · Current workflow status
Retrieved Evidence
Quality SOP, escalation matrix, rework checklist and ERP status rules
Grounded Response
Required escalation, task ownership, deadline, re-inspection condition and cited sections
Business Outcome
The user receives a consistent answer with evidence, while exceptions and approvals remain with the authorized operations team.
ENIGMA can design a managed, private-cloud or self-hosted architecture depending on document sensitivity, latency, integration, cost and ownership requirements.
A controlled managed deployment for organizations that prioritize operational simplicity and faster infrastructure setup.
check_circleManaged retrieval and monitoring
check_circleApproved model and vector services
check_circleScalable application channels
Private networking, controlled storage, identity integration and organization-specific security architecture.
check_circlePrivate data boundary
check_circleEnterprise identity and permissions
check_circleCustom logging and retention
Self-hosted components for organizations requiring deeper infrastructure control and private model options.
check_circleControlled vector database
check_circleOpen-source or private model options
check_circleLinux, containers and monitoring
Each engagement begins with knowledge discovery and ends with a monitored production architecture built around ownership, permissions, integrations and answer quality.
Domains, sources, owners, permissions, freshness and user journeys.
Parsing, chunking, metadata, embeddings, index and retrieval logic.
Web, mobile, portal, CRM, ERP, WhatsApp, API and identity connections.
Evaluation, citations, access control, knowledge gaps and improvement workflow.
The strongest fit is not a company seeking a public FAQ bot. It is an organization with meaningful internal knowledge, multiple teams, recurring questions, sensitive information or a need for consistent evidence-backed answers.
Multiple departments or locations
Large policy or SOP library
Complex product knowledge
Role-based information access
High support or onboarding load
Private deployment requirements
Review users, questions, sources, owners, permissions, systems and knowledge gaps.
Define ingestion, retrieval, model, access control, citations, escalation and hosting.
Clean, classify, tag, version and approve the initial knowledge domains.
Build the index, retrieval logic, identity connection, channels and business-system integrations.
Test answer relevance, citations, access boundaries, edge cases and unanswered questions.
Deploy with monitoring, ownership, synchronization, review and controlled expansion.
The exact architecture depends on data sensitivity, source quality, permissions, languages, usage volume, integrations and deployment requirements.
We’ll identify the highest-value knowledge domains, assess source quality and permissions, and design the right combination of retrieval, AI models, integrations and governance.
