Conversational BI

Conversational BI for executives. Ask in plain English. Get answers in 30 seconds.

Static dashboards report. Conversational BI answers. Type or speak the question your team would normally email an analyst to chase, and the answer arrives in 30 seconds with the underlying numbers attached. The reporting cycle that used to consume one analyst's week becomes a workflow nobody schedules.

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Dashboards Were Never the Answer

A dashboard reports a number. It does not answer a question.

You open the dashboard. You see revenue is down 4 percent week over week. The dashboard does not tell you why. Was it a customer? A product line? A region? A pricing change? A holiday week last year that is not a holiday this year? The dashboard does not know. To find out, somebody has to open three more reports, run a comparison, slice by dimension, and write you back. By the time the answer arrives, the moment for action has passed and you have already moved on to the next question.

The pattern repeats every week, every month, every quarter. The reporting layer keeps being built on the assumption that a chart equals an answer. Charts are not answers. Conversations are answers. Conversational BI puts the conversation where the chart used to be.

A Southern California fresh produce distributor and exporter compressed 62.5 hours per week of executive reporting overhead into 30-second conversational answers. The analyst time did not disappear. It got reallocated to actual analysis instead of report assembly.

What It Looks Like

A walkthrough, not a feature list.

Here is the actual rhythm an executive uses with conversational BI. Try to picture the dashboard equivalent of any of these and notice how much friction is missing.

"Show me revenue last week versus the prior week, by region."

30-second response: the chart, the variance numbers, and a one-paragraph plain-English summary noting that LATAM was up 9 percent and the West region was down 11 percent driven by two large customer accounts.

"Why is West down?"

30-second response: the breakdown by customer, the order frequency change, and the specific accounts that drove the variance, with their order history attached. No second analyst, no second dashboard.

"Are those customers in the at-risk segment?"

30-second response: a cross-reference to the at-risk model, a confirmation that two of three customers are flagged, and the most recent contact log entries from the CRM. The conversation continues until you are satisfied.

"Schedule a Friday standup with the West regional lead and pre-load this thread."

30-second response: meeting created, calendar invite sent, the conversation thread attached as the meeting agenda. The action gets executed, not just reported.

Architecture

How we build it.

Two stack patterns work for SMB and lower-mid-market deployments. The first is Microsoft Copilot Studio over your existing Power BI semantic model and Microsoft 365 environment. The second is Claude (or another frontier model) over a custom semantic layer we build on top of your warehouse, ERP, and CRM. Both deliver the same user experience. The choice depends on which platform you already standardize on and how custom your data model needs to be.

The semantic layer is the work that matters. The conversational interface is the easy part once the semantic model is right. Building the semantic model means: defining the metrics that get asked about, the dimensions that should be sliceable, the joins between systems, and the guardrails that keep the model from inventing answers. We have done this against NetSuite, Sage, Famous Software, QuickBooks, Salesforce, HubSpot, Lawcus, and a half dozen industry-specific systems.

Proof Point

62.5 hours per week, recovered.

A Southern California fresh produce distributor and exporter previously ran a 62.5-hour weekly reporting overhead. Executive team members would email questions to analysts, analysts would build queries, build slides, write commentary, and circulate the deck. By the time the deck was distributed, half the questions had become stale, and a third of the recipients would email follow-up questions that triggered the same loop.

The conversational BI build replaced the entire deck production cycle. Executives now ask in plain English, get the answer with the underlying data, and move on. The 62.5 hours did not vanish; the analysts now spend that time on the genuinely analytical work that used to get squeezed out by the reporting overhead. Read the case study.

Compared to Traditional BI

Tableau, Looker, and Power BI: when each wins.

Conversational BI does not replace dashboard BI. The two products serve different jobs. Dashboards are still right when you need an always-on visual that operators glance at constantly: a fulfillment heat map, a real-time call queue, a finance close progress board. The visual itself is the artifact. Conversational BI wins for the much larger category of ad-hoc executive questions that nobody wants a permanent dashboard for: the comparison this week, the slice this quarter, the diagnosis of a variance.

Tableau, Looker, and Power BI all sell conversational features. The features have improved sharply, and for some customers the off-the-shelf conversational layer is enough. The cases where we get involved are usually one of three: the data model is too custom for the off-the-shelf tool to query reliably, the regulated environment requires a hosting model the SaaS does not support, or the executive team needs the agent to take action (schedule, route, escalate) and not just answer. Off-the-shelf conversational BI rarely does the action half well.

Related

Apps & Dashboards

How conversational BI sits inside the broader build pattern.

Operations Platform

The unified surface conversational BI plugs into.

ERP Modernization

Conversational BI is Phase 3 of the wrap-and-extend pattern.

Heed AI for CFOs

The reporting compression case for finance leaders.

Heed AI for CEOs

Why CEOs ditch the static deck.

Operations Diagnostic

The fastest path to a defensible BI replacement plan.

Blog: Meeting Intelligence

Conversational pattern applied to meetings.

Blog: Anthropic Widget Pattern

How we build the agent surface.

Blog: Historical Data Advantage

Why your data is the moat for conversational BI.

Bring us 3 questions you wish you could ask. We will scope the build.

Twenty minutes on the phone. Three questions you would normally email an analyst about. We will tell you what the conversational BI build looks like for your data.

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