Evaluating and comparing
Proactive Intelligence vs. BI vs. LLM chat: a reference comparison
What each approach is for, where each one stops, and how they fit together.
Short answer
Business intelligence reports on questions you already have. LLM chat answers the prompt you type. Proactive Intelligence discovers what matters across your systems before you know to ask. They are complementary, and they do different jobs.
Key takeaways
- BI is strong for known KPIs. LLM chat is strong for language tasks. Proactive Intelligence is built for discovery.
- The main differences are starting point, cross-system search, validation, and deployment.
- Most organizations will use more than one.
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What each approach is for
Business intelligence (BI). Dashboards and reports for questions someone has defined. Essential for tracking metrics you already know to watch. Dashboards query one source at a time.
LLM chat. Natural-language drafting, summarizing, and answering. Useful for answering a question you can phrase well. It is prompt-driven, so you have to know what to ask, and many tools route data to an external model.
Proactive Intelligence. Discovers what matters across systems from a business direction, matches records across your sources, validates every finding against source records, and recommends with evidence.
Side-by-side
| Capability | Typical BI | Typical LLM chat | Proactive Intelligence |
|---|---|---|---|
| Starts from | A known KPI or report request | A user prompt | A business direction |
| Needs a prompt or query | Yes | Yes | No. Autonomous search, not prompts or queries |
| Cross-system search | One source at a time | Depends on what is provided | Purpose-built |
| Matches the same entity across sources | Limited to what is modeled | Not by design | Shared keys and identifiers, with fuzzy matching where keys are inconsistent |
| Validates findings against source records | No | Not by design | Yes, scored for confidence |
| Traceable to records | The report definition | Often opaque | Every figure maps back to specific records |
| Data gaps | Handled in separate tools | Often not surfaced | Shown with the finding |
| Deployment | Varies | Often an external model | Inside your VPC or on-premises. Nothing leaves, and no external model is called |
This is a general comparison of typical approaches. Individual products vary, so check specifics when evaluating. See also Compare.
When to use which
- Use BI when you know the question and need reliable reporting.
- Use LLM chat when you need drafting, summarizing, or a natural-language interface to content.
- Use Proactive Intelligence when the value is in what you do not yet know to ask, across several systems.
How they fit together
Proactive Intelligence does not replace dashboards or chat tools. It adds discovery on top of the systems you already run. A finding can lead to a new KPI worth tracking in BI.
Where this guide stops
For the point of view behind this comparison, read the blog post "BI answers questions you already have. Chatbots guess. Proactive Intelligence discovers what matters."
Frequently asked questions
What is the difference between BI, LLM chat, and Proactive Intelligence?
Does Proactive Intelligence replace BI?
Can LLM chat do Proactive Intelligence?
Which should I buy first?
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