Flagship Case Study · Distribution · March 12, 2026 · 12 min read
The CEO repriced a merger in the room, on live margin data. We showed this produce distributor what was possible, then we built it.
A Southern California fresh produce distributor and exporter went from static weekly reports to asking plain English questions of live data. Now the executive team prices deals in the moment, including a merger the CEO closed from a tablet in the negotiation itself.
conversational BI layer
Famous, Salesforce, QuickBooks
trade show meetings
content creation time
A multi-LLC produce business running on weekly exports.
The client is a Southern California fresh produce distributor and exporter, multi-LLC structure, sourcing avocados and other produce across grower regions in Mexico and California, distributing through US grocery channels and exporting internationally. The business had grown faster than the reporting layer. The ERP was Famous Software, the sales tracking lived in Salesforce, the accounting lived in QuickBooks, and the executive view of the business was a static weekly report assembled by hand from those three sources.
The CEO ran the company alongside four senior executives: a COO over operations and logistics, a CFO over finance and the multi-entity consolidation, a VP of Sales over the grocery and export channels, and a VP of Operations over grower relationships and supply. Each spent roughly 12 and a half hours per week on context switching, manual data pulls, and decision-blocking lookups. Across the team, that was 62.5 hours per week of senior leadership time spent assembling a picture they should have been able to simply look at.
The dashboards updated on Mondays. By Wednesday they were stale, and by Friday decisions ran on a snapshot that no longer reflected the business. Nobody called it a crisis. It was just how reporting worked.
A merger conversation the static dashboards could not support.
Late in the prior year, merger conversations heated up. The CEO needed real time margin analysis sliced by grower, by product grade, and by region to price the deal credibly. The static dashboards could not deliver that, so the exec team scrambled for four days to build a one-time analysis. By the time it was ready, the buyer's terms had changed. The slice that mattered when the analysis started was not the slice that mattered when it finished.
The CEO came out of that scramble with a clear ask. The next time a merger window opened, the answer to "what is our margin on Hass No. 2 from suppliers in Michoacán in August this year vs last year" needed to take 30 seconds, not four days.
That is when they came to Heed.
Two weeks. Conversational BI on real data.
Every Heed engagement begins with a Proof of Concept against the client's actual data, not a slide deck or a demo on a fake dataset. We spent two weeks building a working conversational BI layer over their live Famous Software, Salesforce, and QuickBooks data.
The architectural choices were deliberate.
- Power BI semantic model. A semantic layer on top of the Famous Software exports that defined every margin, cost, and revenue calculation once, in one place, the way the CFO defined them. No more spreadsheet lineage. The model was the source of truth.
- Microsoft Copilot Studio agent layer. A conversational agent that translated plain English questions into Power BI queries, returned the answer, and showed the source data. Built on Microsoft's enterprise governance fabric, so it inherited the access controls the company already had.
- Anthropic Claude Sonnet for reasoning. The reasoning layer for questions that did not map cleanly to a single query. "Why did margin drop in week 32" is not a SQL question. It is a reasoning question that requires comparing weeks, identifying the variance drivers, and explaining them in business language.
- Power Automate for scheduled syncs. Every morning, the layer pulled fresh data from Famous, Salesforce, and QuickBooks. The semantic model updated. The exec team woke up to a dashboard that was current, not a dashboard that was last week.
- API connectors. Famous Software, Salesforce, and QuickBooks all read into the semantic model through governed connectors. The team did not have to migrate data anywhere. They kept working in the systems they already used.
- M365 SSO and Cloudflare Zero Trust. Every session was authenticated against the corporate directory. Every query was logged. The dashboard surface was gated by Zero Trust at the edge.
Two weeks in, the CEO could ask the system "What is our margin on Hass No. 2 from suppliers in Michoacán in August this year vs last year?" and get an answer in 30 seconds with the source data attached.
Repriced in the room. Closed that afternoon.
About three weeks after the conversational BI layer went live, another merger window opened. The CEO walked into the negotiation with a tablet. When the buyer surfaced a counter-offer that the static reports would have required two days to evaluate, the CEO ran the analysis live on the tablet, in front of the buyer, in under a minute.
The margin analysis showed the offer was undervaluing a specific grower region segment. The CEO repriced the deal in the room based on the live data. The buyer accepted. The deal closed that afternoon.
Heed has been working with the company since.
The same team that had spent four days assembling a one-time margin slice three months earlier now had the answer in the negotiation itself. The dashboard moved from reporting tool to decision instrument.
Five role-tuned dashboards. One conversational layer.
Phase 1 was scoped to deliver executive intelligence to the five-person leadership team. Each executive received a dashboard tuned to their role, all backed by the same conversational layer over the same semantic model.
CEO dashboard
Total margin by entity, deal pipeline, executive KPIs, and the conversational query box that handles ad hoc questions. The view that won the merger negotiation.
COO dashboard
Logistics, fulfillment, in-transit inventory, and grower region supply by week. Replaces a Monday spreadsheet that took two hours to assemble.
CFO dashboard
Multi-entity consolidation, AR aging, cash position, and margin by product line. Pulls live from QuickBooks and the Power BI semantic model.
VP Sales dashboard
Grocery and export channels by customer, deal velocity, and margin by account. Salesforce-backed with the semantic model overlay.
VP Operations dashboard
Grower relationships, supply by region, quality grades by week, and the comparison views the team used to use spreadsheets for.
The conversational layer
One Microsoft Copilot Studio agent backed by Claude Sonnet. Every executive can ask the same question of the same data and get a consistent answer with source citations.
From executive dashboards to multi agent trade show automation.
With the executive decision layer live, the conversation moved to growth. Trade shows were the company's biggest annual sales event, and the team ran them the way most distributors do: a four-week sprint of content production, outreach, and meeting bookings, all by hand.
We built a multi agent trade show automation layer on top of the same governance and access fabric as the executive dashboards.
- The 45-day pre-show trigger. Forty-five days out, an agent kicks off the pre-show motion, generating segmented target lists from the Salesforce data.
- The content creation agent. Generates emails, LinkedIn posts, and one-pagers tailored to each segment, with the brand voice guardrails and the product portfolio context baked in. Reduced content creation time by 80 percent.
- The LinkedIn outreach agent. Runs the personalized outreach motion, books meetings, and drops them into the team's calendars with the conversational BI dashboard linked for prep.
Result: 200 percent increase in qualified meeting bookings at the next trade show, with 80 percent less content creation time, all running on the same governance fabric as the executive dashboards.
Senior leaders got their week back. Here is the proof.
Phase 1 Math
- 5 executives × 12.5 hours per week saved = 62.5 hours per week recovered
- 62.5 hours per week × $200 per hour blended exec rate × 50 weeks
- = $625,000 in recovered capacity per year
- $45,000 invested in Phase 1 build
- Payback in 4 weeks
The merger deal that closed in the negotiation room and the trade show extension that tripled qualified bookings are not in the $625K. Those are upside.
The second order effects make the math stronger. Decisions stopped waiting for reports. Friday afternoons stopped being export and reconcile sessions. The exec team got to do exec work. The merger closed. Trade show ROI tripled.
From weekly reports to a live decision layer.
The behavioral change was immediate. The Monday morning weekly report meeting got shorter because the team had already seen the data. The Friday afternoon export and reconcile sessions disappeared. Questions that used to start with "let me get back to you on Monday" started getting answered in the meeting.
The CFO consolidation got faster. Instead of waiting for QuickBooks exports to land in a spreadsheet, the multi-entity view was live in the dashboard. The VP of Sales started running her territory reviews against live grocery channel data instead of last week's snapshot. The VP of Operations stopped asking growers to send updated supply numbers because the dashboard had them.
The CEO's calendar shifted. Instead of being a series of decision deferral meetings, it became a series of action meetings. The dashboard answered the questions that used to require a meeting. The meetings were for the questions that required judgment.
Microsoft enterprise fabric. AI-native reasoning. Zero Trust at the edge.
Every component was chosen for governance, auditability, and the company's existing Microsoft 365 footprint. Nothing was ripped out. The new layer wrapped what was already there.
Microsoft Copilot Studio
The conversational agent layer. Translates plain-English questions into governed queries against the semantic model.
Power BI semantic model
One canonical layer where margin, cost, and revenue are defined once. The single source of truth for every dashboard and every query.
Anthropic Claude Sonnet
Reasoning layer for questions that require comparison, explanation, or business-language interpretation rather than a single query.
Power Automate
Scheduled syncs from Famous, Salesforce, and QuickBooks. The dashboards refresh every morning before the executive team logs in.
API connectors
Famous Software, Salesforce, and QuickBooks Online connectors. Read-only against the source systems. No data migration required.
M365 SSO and Cloudflare Zero Trust
Every dashboard surface is gated by Zero Trust at the edge. Every session is authenticated against the corporate directory. Every query is audit-logged.
The Heed Method
Every engagement starts with a POC against your real data.
The dashboards that closed the merger deal did not start with a discovery deck. They started with a two-week sprint against the actual Famous Software, Salesforce, and QuickBooks data. The POC validated the architecture before anyone signed a production budget.
If your executive team is spending hours per week assembling the picture they should be able to look at, that pattern has a fix. The fix usually pays for itself in the first month.
Keep reading.
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How conversational agents turn meetings into structured business knowledge.
Read the post →Unified Operations Dashboard
The landing page for the executive intelligence offering this case study built.
See the offering →Heed AI for CFOs
The CFO playbook that the produce distributor's CFO uses every morning.
Read the playbook →Heed AI for CEOs
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Read the case study →Your executive team should not be assembling reports. Book the diagnostic.
If your senior team spends hours per week building the picture they should be able to look at, the conversational BI layer that solved this for the produce distributor will do the same for you. The 30-day diagnostic produces the math before you commit a dollar.