Documentation
Guides, comparisons, and how-tos.
Practical, plain-English explanations of secure multi-model AI, and how ChatLite puts it to work.
Guide
What is a multi-model AI workspace?
A plain-English definition of multi-model AI workspaces, why teams adopt them, and how ChatLite implements one.
Guide
AI guardrails explained
What AI guardrails are, the risks they mitigate (PII leaks, prompt injection), and how to apply them across a team.
Comparison
ChatLite vs. single-model AI tools
A factual comparison of a governed, multi-model workspace versus single-model chat tools for teams.
How-to
How to run deep research in ChatLite
A step-by-step guide to running a deep research report, from question to cited brief.
Guide
Why enterprises need a multi-model AI workspace
Model diversity, governance, and avoiding vendor lock-in: why one governed multi-model workspace beats scattered single-model tools.
Guide
Self-hosting enterprise AI: control, compliance, and data residency
When and why enterprises run AI in their own cloud or data center, and what self-hosting ChatLite delivers.
Guide
Custom integrations: connecting enterprise systems to AI
How custom integrations and connectors ground AI in the systems, databases, and tools your organization already runs.
Guide
Connecting custom agents in one AI workspace
Bring your own agents and tools into a single governed plane, orchestrated alongside chat, research, and image generation.
Guide
Enterprise data feeds: keeping AI grounded in your knowledge
Why live and batch data feeds matter for accurate, current, organization-specific answers.
Guide
Why AI security matters for the enterprise
The risks of ungoverned AI (data leakage, prompt injection, shadow AI) and the controls that mitigate them.
Guide
Data residency and governance for enterprise AI
How to keep AI usage compliant across regions with residency controls, audit trails, and access governance.
Comparison
Build vs. buy: customising an enterprise AI platform
The trade-offs between building AI infrastructure in-house and adopting a customisable, self-hostable platform.
Guide
Model routing and cost control in multi-model AI
Routing each task to the right model, and the governance that keeps spend predictable at enterprise scale.
How-to
An enterprise AI rollout checklist
A practical, step-by-step checklist for rolling out governed AI across an organization.