Using AI to Improve SaaS Onboarding and Activation
How SaaS companies use AI to get new users to value faster: guided setup, data import, in-app assistants and personalised…
Why Your Business Needs an Enterprise GenAI Platform
Scattered AI tools create cost, security and quality problems. Here is why mid-size and large organisations are building a central GenAI platform.
In most organisations, generative AI arrives bottom-up. Marketing uses one tool, engineering another, someone in finance pastes spreadsheets into a free chatbot. It feels productive — until security, legal or the CFO looks closer.
The problems with AI sprawl
- Data leakage: confidential information sent to consumer tools with unclear terms
- Duplicated spend: many overlapping subscriptions and no volume pricing
- Inconsistent quality: no shared prompts, guardrails or evaluation
- No visibility: nobody knows what AI is being used for, by whom, or with what results
What an enterprise GenAI platform provides
- A secure gateway to approved models with enterprise terms
- Model routing to send each task to the best-value model
- Shared knowledge connectors to SharePoint, Google Drive, Confluence and databases, respecting permissions
- Guardrails for PII redaction, content safety and policy enforcement
- Usage analytics and cost allocation by team and use case
- Reusable building blocks so new use cases launch in days, not months
Build, buy or blend?
Off-the-shelf enterprise assistants cover general productivity. A platform layer becomes valuable when you want custom applications, data residency (for example in the UAE or India), model choice and tight integration with internal systems. Many organisations blend both.
Getting started
Begin with an AI usage audit, define approved models and data policies, then stand up a minimal gateway and one or two high-value internal applications. Expand from there.
See how we build enterprise GenAI platforms with security and governance in mind.
