An enterprise AI platform for secure, governed operations at scale.
Build and operate AI agents, applications and workflows around your own data, tools, models and infrastructure, then scale them across teams with governance built in.
More than a chatbot. An operating foundation for enterprise AI.
A complete enterprise AI platform needs to work with internal data, existing systems, security controls and real operating processes from the start.
01
Complete data control
Keep control over where information lives, how it is accessed and how AI services use your enterprise knowledge.
02
Enterprise governance
Apply access controls, policies, guardrails, tracing and oversight across AI services without slowing delivery.
03
Scale without fragmentation
Start with focused use cases, then expand across teams and workflows on one shared AI operating foundation.
Turn AI adoption into a structured operating capability.
Connect workforce adoption, AI applications and governance in one model instead of creating isolated pilots for every team.
Workforce layer
Give teams an everyday AI assistant for conversations, knowledge, tasks, reminders, files and connected work.
Application layer
Use cognipeer Studio to build and orchestrate AI agents, applications and workflows that connect enterprise data, APIs, CRMs, ticketing systems and internal tools.
Governance layer
Use cognipeer Console to manage models, providers, access, guardrails, observability, usage and infrastructure from one AI control plane.
AI services tailored to business operations.
Build around the workflows your organisation already depends on, rather than forcing teams into a generic AI experience.
Enterprise AI agents
Create specialised AI peers for sales, HR, IT, support, development and other business functions.
Enterprise Knowledge & RAG
Connect AI to enterprise knowledge through retrieval, embeddings, vector search and grounded response generation.
Agentic workflows
Enable AI to call APIs, trigger actions, update systems and support real task execution.
AI Infrastructure & MLOps
Standardise model access, serving, tracing, monitoring and operational controls across enterprise AI workloads.
The infrastructure behind governed AI at scale.
Console brings the operational layers of enterprise AI together so platform, IT and AI teams do not have to manage models, retrieval, observability and governance as disconnected systems.
RAG & Knowledge
Retrieval, vector indexes, knowledge engines, memory and document-backed AI experiences.
Model Gateway
Manage multiple model providers through a shared gateway instead of locking workloads to one model.
MLOps / LLMOps
Standardise model operations, provider configuration, usage, monitoring and performance management.
Observability
Trace sessions, runs and agent activity while monitoring latency, usage and operational behaviour.
Guardrails & Policy
Apply policy controls, guardrails, PII protection, access rules and audit-ready governance.
Flexible Deployment
Support cloud, private and self-hosted environments according to enterprise architecture requirements.
A clear path from use case to production.
cognipeer supports enterprise AI implementation from initial use-case design through integration, rollout and continuous improvement.
Discuss your AI roadmap01
AI strategy & use-case design
Assess readiness, prioritise feasible use cases and define a practical implementation roadmap.
02
Knowledge & model design
Design retrieval, model selection and output behaviour around your enterprise context.
03
Integration & workflow automation
Connect AI to the systems, APIs and tools your teams already use.
04
Rollout & continuous improvement
Support deployment, adoption, performance review and ongoing optimisation as AI usage grows.
Fit AI around your environment, not the other way around.
Deployment, onboarding and ongoing support can be shaped around your infrastructure, security model and organisational requirements.
Private deployment options
Support cloud, private and self-hosted enterprise environments where infrastructure, data residency or operational control is required.
Guided onboarding
Get support with configuration, data connections, integrations and adoption planning.
Tailored architecture
Shape models, workflows, controls and integrations around your operating requirements.
Ongoing support
Continue improving AI services with operational guidance, optimisation and room to scale.
Adapt AI to the way your sector actually works.
cognipeer supports regulated, process-heavy and data-driven environments where context, control and reliability matter.
Move from scattered AI experiments to a governed operating model.
Build, deploy and scale enterprise AI with the control, flexibility and infrastructure your organisation needs.