A unified architecture for enterprise AI assistants.
Mentoros is a governed AI layer between your knowledge, your systems, and the people who need access to them — customers, support teams, and internal teams. One architecture, multiple deployment surfaces, shared platform controls.
Knowledge & Systems
- Documentation & SOPs
- CRM, ticketing, commerce
- Internal tools & APIs
- Structured & unstructured data
Mentoros
- Assistant runtime
- Admin console
- Intelligence layer
- Governance & policy
Assistants & Channels
- Customer web & app
- Support workflows
- Internal team tools
- Embedded experiences
Between your systems and the people who use them.
Knowledge and operational systems flow in. Customer, support, and internal surfaces flow out. Mentoros is the governed boundary in between — grounding responses in approved sources, enforcing policy centrally, and turning every interaction into operational signal.
Knowledge & Systems
- Documentation & SOPs
- CRM, ticketing, commerce
- Internal tools & APIs
- Structured & unstructured data
Mentoros
- Assistant runtime
- Admin console
- Intelligence layer
- Governance & policy
Assistants & Channels
- Customer web & app
- Support workflows
- Internal team tools
- Embedded experiences
Three layers, one platform.
Mentoros is structured as three coordinated layers — runtime, control, and intelligence. Each is operated independently. Together they define a complete, governed AI deployment.
AI Assistants
Production assistants for customer-facing, support, and internal-facing surfaces, grounded in approved knowledge and scoped by deployment context.
- Customer-facing, support, and internal assistants
- Retrieval-grounded, context-aware responses
- Tool-use and actions against connected systems
Admin Console
Shared platform infrastructure for configuration, knowledge, governance, and oversight — across every assistant and every deployment.
- Workspace, role, and access management
- Knowledge curation and source control
- Policy, persona, and guardrail configuration
Intelligence Layer
Conversations are converted into structured signal — surfacing gaps, scoring quality, and feeding continuous improvement back into the platform.
- Behavioral and intent analytics
- Knowledge gap and coverage detection
- Natural-language access to operational data
The same platform, applied across the enterprise.
What changes between deployments is the surface, the connected sources, and the access policies. The platform underneath does not.
Customer-facing
Mentoros Commerce
AI assistant for digital commerce — product discovery, guided shopping, order assistance, and post-purchase support across web and app.
Connected sources
Customer & agent-facing
Mentoros Support
AI assistant for customer support — instant answers, ticket deflection, agent assist, and SLA-aware escalation built on your existing support stack.
Connected sources
Internal-facing
Mentoros Internal
AI assistant for internal teams — knowledge retrieval, cross-system reasoning, and natural-language access to operational data, governed by role.
Connected sources
Knowledge, configuration, and analytics are managed centrally — across customer, support, and internal deployments alike.
Augments your stack. Does not replace it.
Mentoros operates inside the environment you already run — connecting to systems of record, knowledge sources, and custom applications, while respecting the boundaries you define.
Knowledge sources
- Documentation portals
- Internal wikis
- SOPs and policies
- Help and support content
Systems of record
- CRM
- Ticketing
- Commerce platforms
- HRIS, ITSM, finance
Operational data
- Business intelligence
- Analytics warehouses
- Event and product data
- Conversation history
Custom & APIs
- Internal applications
- Public and private APIs
- Webhooks and triggers
- Tool-use endpoints
Read, retrieve, or act — scoped per deployment, governed per role.
Operational control across every deployment.
Configuration, access, and oversight live where the assistants live — operated day-to-day from the same console that runs them.
Configuration & policy
Personas, scopes, refusal rules, and per-deployment policies — managed from one console.
Access & permissions
Role-based access, workspace isolation, and per-deployment permissions across teams.
Conversation review
Inspect, replay, and annotate real conversations to validate behavior and improve assistants.
Audit & oversight
Audit-grade logging of configuration, access, and knowledge changes — by team and deployment.
Every interaction makes the platform sharper.
Mentoros is not only a runtime. The intelligence layer converts conversations into operational signal that flows back into knowledge, configuration, and product decisions.
Interactions
Real conversations across customer-facing, support, and internal surfaces.
Analytics
Intent, resolution, sentiment, and behavior patterns at scale.
Insight
Knowledge gaps, friction points, and emerging questions surfaced automatically.
Optimization
Knowledge, policy, and configuration updates — applied centrally and continuously.
Why this architecture works for enterprise teams.
One platform across every track
Customer-facing, support, and internal deployments on a single architecture — no parallel stacks to maintain.
Live inside the existing stack
Connects to the systems and knowledge already in production. No re-platforming to start.
Governed and instrumented by default
Operational control and intelligence are part of the platform — not a separate enterprise tier.
Pilot to production, in one path
Launch a focused use case, then expand across tracks on the same architecture.
Let’s map Mentoros to your environment.
Walk through deployment context, connected systems, governance requirements, and the use cases that matter most — with the people who build the platform.