While You Wait Days for Reports, Quarrio Delivers 100% Accurate Answers in Under Two Seconds

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While You Wait Days for Reports, Quarrio Delivers 100% Accurate Answers in Under Two Seconds

May 25, 2026

In a recent The Rise of Conversational Analytics podcast conversation, Quarrio's Dylan Gray made the case for why conversational analytics, not dashboards or GenAI, is finally the answer to the data access problem enterprises have been trying to solve for 50 years.

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Somewhere in your business right now, a sales rep is waiting two days for a win-rate report. A VP is building a board presentation from a Salesforce export, a VLOOKUP, and a prayer. A regional manager just asked their analyst for the same follow-up report they requested last week.

None of this is data strategy. It's data delay, and it's costing you revenue.

In a recent episode of The Rise of Conversational Analytics podcast Quarrio’s VP of Sales Operations Dylan Gray laid out exactly why this is happening, and more importantly, why it no longer has to.

The Problem No One Has Solved in 50 Years

The database was invented in the 1970s. Since then, organizations have invested billions in data lakes, CRM systems, ERP platforms, business intelligence tools, and now AI. And yet the same fundamental problem persists: most business users still can't get a good answer from their own data without waiting for someone else to get it for them.

As Dylan puts it:

"That is pretty much every company apart from maybe the odd mom and pop on the planet and they still haven't solved it. And we're still trying to solve it 50 years on."

The tools that were supposed to fix this – Tableau, PowerBI, custom dashboards – require data scientists who understand the structure of the data, skilled BI developers to build the visualizations, and days or weeks to turn around a single report. Ask a follow-up question and the clock starts again.

The result? Business leaders make decisions based on gut feel, outdated spreadsheets, or incomplete information – not because the data doesn't exist, but because accessing it is still too slow, too hard, and too dependent on specialists.

Why GenAI Alone Isn't the Answer

Many executives responded to this problem by investing in generative AI – ChatGPT, Copilot, Einstein, Agentforce, etc. It's an understandable move. But it introduces a different problem: accuracy.

Generative AI is probabilistic. It works by predicting the statistically most likely answer based on patterns in data. Dylan explains:

"You ask a nice question… it does a mathematical calculation and says statistically this is the most likely answer. Somewhere between 65 and 85% accurate."

That's acceptable for content generation. It is not acceptable when you're making a capital allocation decision, forecasting revenue, reporting to a regulator, or briefing a board. And the enterprise world is starting to figure that out.

According to MIT NANDA's The GenAI Divide: State of AI in Business 2025 report, despite $30 to $40 billion in enterprise investment in generative AI, 95% of organizations report seeing little to no material ROI. A February 2026 NBER working paper, Firm Data on AI, reinforces this disconnect. Surveying nearly 6,000 senior executives across the US, UK, Germany, and Australia, the authors find AI has delivered just a +0.29% productivity gain after three years of adoption, with 89% of executives reporting no measurable impact on sales per employee. Meanwhile, the CEO of Salesforce has signaled a strategic shift toward a more deterministic foundation to underpin Agentforce and Einstein. The AI wave hasn't failed. It's just exposed the gap between AI that talks and AI that delivers.

What Quarrio Does Differently

Quarrio is deterministic AI, a fundamentally different architecture from any LLM-based tool on the market.

Here's what that means in practice:

You ask a business question in plain English. No SQL. No data structure knowledge required. No training needed.
Quarrio translates it into a verifiable database query against your live structured data: Salesforce, SAP, Oracle, ERP, data warehouse, or any JDBC-compatible source.
You get the answer in under two seconds, with the exact SQL code so you or your IT team can independently verify the result.
The answer is 100% fact-based. If the data exists, you get it. If it doesn't, Quarrio says so. If the question isn't understood, it says that too. At no point will you receive an answer that cannot be verified.

Dylan's test is simple:

"You could ask the same thing 100 times of Quarrio and you will get the identical answer."

What This Looks Like in the Field

Imagine you're a VP of Sales walking into a Monday morning pipeline review. Instead of waiting for a deck your analyst built over the weekend – from data that may already be 48 hours stale – you pull out your phone and ask:

"Show me top 10 customers by revenue."

Instantly, a list appears.

"Which of these bought a generator in the last 90 days?"

Instantly, filtered.

"What was the win rate for each of those deals?"

Instantly, done.

That's not a demo script. That's Quarrio running against your live Salesforce data, on your phone, in real time, with complete auditability. Every answer can be exported to Excel, shared with the team, or pinned to a personal dashboard - instantly.

For Salesforce-heavy organizations in particular, the value is immediate. Dylan – who spent 10 years running a Salesforce consulting firm and has supported up to 10,000 salespeople across global enterprise deployments – is direct about what this means:

"You can empower an entire sales organization and you can brief a brand new VP of Sales in less than 20 minutes."

Not in a week of onboarding. Not after IT configures a dashboard. In 20 minutes.

The ROI Case That Closes Itself

Many AI tools ask buyers to take it on faith that value will materialize. Quarrio's ROI argument is straightforward enough to walk into a CFO meeting with. Dylan frames it this way:

"You've got a $100 million organization. I am pretty comfortable that if we implement Quarrio for sales, we can move your win rate 3% in under a year. Well, 3% of $100 million is $3 million. We don't cost $3 million."

For a sales leader or revenue operations exec, that math ends the conversation. You get AI, data unification, performance improvement, and a return on your investment in under a year – and you're not betting on probabilistic outputs to get there.

The payback clock also starts fast. Quarrio is typically up and running in 4-6 weeks, requiring no changes to your existing data infrastructure, no new security models, and no expensive transformation projects.

The Security Objection - Already Handled

The first thing many security-conscious enterprise buyers ask is: "What happens to our data?"

With Quarrio, the answer is architecturally simple: your data never leaves your organization.

"We only install it inside your security footprint. The security is your existing security."

Quarrio operates entirely within your enterprise perimeter. There's no data export to a third-party model, no training on your proprietary information, no exposure to external systems. Your questions and your data stay inside your walls, always.

The contrast with uncontrolled GenAI tool adoption is stark. When employees use a public tool like ChatGPT with sensitive business data, that information enters an external ecosystem. With Quarrio, that risk doesn't exist, by design. Quarrio is PCII-DSC and SOC 2 compliant, and for regulated industries including financial services, healthcare, manufacturing, and government, this architecture isn't just preferable. It's essential.

Quarrio Is a Complement, Not a Replacement

One of the most common objections Dylan encounters in the field: "We already have AI."

The answer isn't competitive. It's additive.

Quarrio doesn't replace Salesforce, Tableau, PowerBI, or your existing GenAI investments. It plugs into them, provides the 100% accurate, fact-based data layer underneath them, and makes every downstream system more trustworthy. Think of it as the "Intel Inside" for your enterprise data, the verified intelligence layer that everything else runs on top of.

For organizations with heavy Salesforce deployments: Quarrio connects natively, operates alongside Einstein and Agentforce, and gives every person in the organization direct, verified access to the same source of truth.

The Two Mistakes That Are Holding Your Organization Back

Dylan's final message is a challenge to any executive who considers themselves data-driven.

Mistake #1: Unresolved data identity across systems

In most large organizations, the same physical item, a product SKU or a customer entity, has different names and IDs across different systems. Until that's resolved, every AI or BI tool built on top of that data is running on a flawed foundation. Quarrio helps solve this through its unified namespace, a deterministic layer that gives every data item a single, consistent identity across all your systems. For a deeper look at how this works, read The AI That Can't Be Wrong on the Quarrio blog.

Mistake #2: Investing in AI without a measurable return

McKinsey,MIT and NBER have all flagged that the overwhelming majority of AI projects are not returning their investment. The cause isn't AI itself, it's deploying probabilistic tools in situations that demand deterministic answers. Quarrio is built specifically for the use cases where accuracy is non-negotiable and the outcome is measurable. As Dylan puts it:

"You're going to get AI, data unification, performance, competitive advantage, and a return on your money in under a year. In which case, why are you doing anything else?"

The Bottom Line for Sales Leaders

If your team is still waiting days for reports, reconciling Salesforce pipeline against actuals manually, or relying on analysts to answer questions that should take two seconds, Quarrio was built for you.