Conversational Analytics
Chat with your data, properly - we build conversational analytics over a governed semantic layer, so a typed question returns the same correct, governed answer every time.
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Ask Anything, Trust the Answer: Australia's Conversational Analytics Specialists
It is the demo every executive asks for: type a question in plain English and get a correct, governed answer from company data. Done badly - an LLM generating raw SQL against your tables - it returns a different number every time and quietly erodes trust. SureLogic builds it properly. We put the language model over a governed semantic layer, with agreed definitions, row-level security and an evaluation harness, so the same question always returns the same right answer. This is the commercial application of the semantic-layer thesis and the most demo-able capability we offer: natural-language analytics your executives will actually trust, not a party trick that contradicts itself.
Same Right Answer
Built on a governed semantic layer, the same question always returns the same correct number, so conversational analytics earns trust instead of contradicting itself run to run.
Ask in Plain English
People ask questions in natural language and get answers grounded in your agreed definitions, so the barrier between a business question and a trustworthy answer drops to a sentence.
Governed Answers
Row-level security means each person's answers reflect only the data they are allowed to see, so the same rules that protect your dashboards apply to every question typed.
Your Definitions
Answers use your organisation's measures - your revenue, your margin, your active customer - rather than whatever the model improvises, so they match the logic your reports already use.
Proven Accurate
An evaluation harness measures answer accuracy against known-correct results, so quality is a number you can track and improve, not a hopeful demo that drifts in production.
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Our Conversational Analytics Services
Governed Semantic Layer Foundation
Build conversational analytics on a foundation, not raw SQL. The reason most chat-with-your-data demos fail in production is that they generate SQL directly against tables, with no shared definitions, so the same question returns different numbers. We put a governed semantic layer underneath - the agreed metrics, relationships and business logic - so the model reasons over meaning rather than guessing at schema. This is the difference between a reliable analytics assistant and a confident random-number generator.
Natural Language Over Your Definitions
Let people ask in plain English and get your definitions, not the model's. We connect the language model to your semantic layer so a typed question is answered using your organisation's agreed measures - your definition of revenue, margin, active customer - rather than whatever the model improvises. Users ask naturally and get answers grounded in the same logic your dashboards use. The barrier between a business question and a trustworthy answer drops from a data request to a sentence.
Row-Level Security & Governed Answers
Make every answer respect who is asking. An analytics assistant that ignores security is a data leak with a chat box. We enforce row-level security and governance so each user's conversational answers reflect only the data they are permitted to see - the same rules that protect your reports apply to the questions people type. Executives get the whole picture, regional managers get their region, and nobody gets numbers they were never meant to access.
Evaluation Harness & Consistency
Prove the same question returns the same right answer. Conversational analytics is only valuable if it is consistent, so we build an evaluation harness that tests the system against a curated set of questions and known-correct answers. It catches the cases where the model drifts, misreads intent or contradicts itself, before users do. You get measurable answer accuracy and a repeatable way to improve it, turning a flaky demo into a system executives can rely on for decisions.
Executive Demo & Rollout
Take it from a demo executives love to a capability they use. We package the working solution for rollout - the interface, the governed answers, the security and the evaluation - and support adoption across your leadership and teams. Because it is built on your semantic layer, it extends naturally as you add metrics and sources. The most requested AI demo becomes a genuine self-service capability, not a one-off wow moment that never makes it into daily decisions.
190+ Australian organisations Choose Surelogic.
570+ Successful Projects
We bring deep architectural experience to every engagement, having engineered hundreds of secure, scalable data platforms and semantic models across Australian industries.
100% Australian Owned
We never farm your data assets out to offshore teams. Our team is entirely Australian-based, guaranteeing flawless communication, immediate timezone alignment, and strict data sovereignty.
Your Tenant, Your IP
We build directly inside your cloud environment so the infrastructure is entirely yours - including semantic models, custom code, and IP. You maintain absolute control without vendor lock-in.
Partnering with SureLogic was a game-changer for Cupid Media. They turned our outdated reporting process into a modern, data-driven strategy that delivered real-time insights and cost savings we didn’t think possible. Their expertise in BigQuery, Tableau and machine learning brought immediate value to our business.
Ben Snart
Chief Product Officer, Cupid Media
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Our Proven Conversational Analytics Framework
Our senior specialists ground natural-language analytics on your semantic layer, prove it is consistent, and roll it out to people who will actually use it.
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Semantic Foundation & Use Cases
We define the questions your people most want to ask and the governed semantic layer needed to answer them - the agreed metrics, relationships and security. Where the foundation exists we build on it; where it does not, we establish it. You receive a clear plan grounding conversational analytics in your definitions rather than raw SQL.
Build & Evaluate
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We connect the language model to your semantic layer, enforce row-level security, and build the conversational interface. An evaluation harness tests answers against known-correct results until the system is consistent and accurate. The result is natural-language analytics that returns the same right answer to the same question, respecting who is asking.
Demo, Roll Out & Extend
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We package the solution for rollout, support adoption across your leadership and teams, and hand over the evaluation process. Because it is built on your semantic layer, it extends naturally as you add metrics and sources. The demo executives love becomes a governed self-service capability used in real decisions, not a one-off wow moment.
Conversational Analytics FAQs
What is conversational analytics or chat with your data?
Conversational analytics lets people ask questions of company data in plain English and get correct, governed answers, instead of waiting on an analyst or building a report. Done properly, it is a language model reasoning over your governed definitions rather than generating raw SQL, so answers are accurate, secure and consistent. It is the most requested AI capability among executives, because it turns a business question into an answer in a sentence.
It is the application of a semantic layer - see our semantic layer consulting page.
Why do AI tools give different answers to the same question?
Because most generate SQL directly against your tables with no shared definitions, so the same question is answered differently depending on how the model interprets the schema that time. Without an agreed definition of revenue, margin or active customer, the model improvises - and improvises differently on each run. The fix is a governed semantic layer underneath, so the model reasons over your definitions and the same question always returns the same right number.
Isn't this just letting an LLM write SQL against our database?
No - and that approach is exactly what makes most chat-with-your-data projects fail. Raw text-to-SQL has no shared business logic, no consistency and weak security. We build conversational analytics over a governed semantic layer instead, so the model answers using your agreed metrics, honours row-level security, and returns consistent results. It is the difference between a reliable analytics assistant and a confident random-number generator pointed at your database.
Is it secure - will people see data they should not?
No - we enforce row-level security and governance so each person's answers reflect only the data they are permitted to see. The same rules that protect your dashboards apply to the questions people type, so executives get the whole picture and regional managers get their region. An analytics assistant that ignored security would be a data leak with a chat box; governed answers are built in from the start.
Security rests on governance - see our trusted data architecture and governance page.
How do we know the answers are actually right?
We build an evaluation harness that tests the system against a curated set of questions with known-correct answers, so consistency and accuracy are measured rather than assumed. It catches the cases where the model drifts or misreads intent before your users do, and gives you a repeatable way to improve. You get measurable answer quality, which is what turns conversational analytics from a flaky demo into a system executives trust for decisions.
78% of new clients engage us for recurring data partnerships
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U11002/1328 Gold Coast Highway,
Palm Beach, QLD, 4221, Australia