8 September 2026
New tool gives analytics and insights teams instant, source-traceable answers from their own verified data, addressing growing distrust of generative AI in enterprise decision making
Relative Insight, the deterministic AI platform for customer intelligence, today announced the launch of Zayker, an AI assistant that lets analytics and insights teams query their voice of customer data in plain language and receive answers grounded entirely in verified, auditable analysis.
Built on Evidence, Not Generated Narrative
Unlike general-purpose AI assistants, which generate responses from raw, unstructured data and can produce different answers to the same question, Zayker draws only from analysis that has already been processed and verified by Relative Insight’s deterministic engine.
Every answer includes a direct citation back to its source report and underlying data, giving teams a way to verify, defend, and act on AI-assisted findings with confidence.
A Widening Trust Gap in Enterprise AI
The launch responds to a widening trust gap in enterprise AI. According to insightsoftware’s 2026 research [1] , only 51% of data and analytics leaders fully trust the AI-generated outputs their own teams produce. Separate research from the Financial Times [2] found that 75% of business leaders have held back a decision because they could not verify the AI behind it.
We kept hearing the same thing from analytics leaders: their teams were already using AI, but they’d stopped trusting what it told them
Ben Hookway, CEO of Relative Insight
The problem was never whether AI could summarize customer feedback quickly. It’s that speed without evidence just moves the risk downstream, onto whoever has to defend that answer in a room full of stakeholders. Zayker exists because we believe the two shouldn’t be a trade-off. You should be able to get an answer in seconds and still know exactly where it came from.”
How Zayker Works
Zayker sits on top of the existing Relative Insight platform, meaning customers do not need to migrate data or rebuild reporting infrastructure to use it. Once a data source has been analyzed and verified by the platform, Zayker becomes immediately queryable, allowing stakeholders across an organization – not just the analytics team – to ask questions and receive sourced answers without waiting for a report to be built.
Key capabilities include:
- Lower cost than general-purpose AI. Because Zayker is purpose-built for customer intelligence queries rather than general reasoning, it requires a fraction of the compute cost of running equivalent queries through enterprise LLM tools.
- Segment-level accuracy. A curated, ontology-based report library ensures smaller but important customer segments aren’t lost in majority-weighted responses.
- Consistent, repeatable answers. Because Zayker draws from deterministic analysis rather than generating narrative on the fly, the same question produces the same answer every time, regardless of who asks or when.
- Source-level evidence. Every answer carries a direct trail back to the specific report, statistic, or verbatim it was built from.
That’s the bar analytics teams should be holding AI tools to. Not ‘does this sound plausible’, but ‘can I get the same defensible answer tomorrow, and the day after that.’ That’s what we built Zayker to do.
Zayker is available now to existing Relative Insight customers and is being rolled out to new customers via a scoped proof-of-concept engagement. Organizations interested in seeing Zayker on their own data can book a personal demo.
Consistent Answers, Every Time
In an early demonstration of the tool, an analyst was able to ask Zayker why a specific region was underperforming against network averages, receive a sourced answer within seconds, and confirm the same finding independently against call transcript data, all without leaving the chat interface.
“What convinced me wasn’t a single clever answer. It was asking the same question twice, a week apart, and getting the same evidence both times,” added Ben.
[1] [2] Link to all research cited here
