The Background
Every year, consumer goods suppliers lose millions of dollars to retailer deductions: chargebacks, compliance fees, shortage claims, and pricing adjustments that Amazon, Walmart, Target, Home Depot, Kroger and dozens of major retailers apply automatically and at scale. For most suppliers, the response is a team of people manually logging into retailer portals, pulling documents, and filing dispute after dispute.
iNymbus was built to change that. The Houston-based fintech company uses cloud-based robotic process automation to handle the entire deduction dispute process on behalf of CPG manufacturers and distributors, supporting more than 50 major retailers at processing speeds up to 30 times faster than human teams, at 80 to 90% lower cost. Their clients include some of the most recognizable names in consumer goods, companies shipping to BIC, Compana Pet, Fanatics, Hanes and Igloo, who rely on iNymbus to recover revenue that would otherwise disappear into manual backlogs.
The suppliers iNymbus serves are running lean finance teams against opponents with enormous technological firepower. They need a partner who can match Amazon and Walmart's automation with automation of their own. iNymbus built that. The next problem was making sure those suppliers found iNymbus when they went looking for help.
The Challenge
The Supplier on the Other Side of a Deduction Notice
When a CPG finance team gets hit with a deduction, they have a narrow window to dispute it before the claim expires. Their team is already stretched, their processes are manual, and the retailers they are disputing have systems designed to process denials faster than any human team can respond. Accounts receivable managers at mid-size suppliers were spending hours per week per retailer just to keep up, often losing claims because the paperwork took too long.
Those finance teams were doing their vendor research the same way most buyers do today: by asking an AI. "What is the best deduction management software?" "How do CPG suppliers automate retailer chargebacks?" Those queries were landing on ChatGPT, Gemini, Perplexity, and Google AI Overviews, and the answers those engines returned were shaping shortlists before a single sales call happened.
Invisible Where Decisions Were Starting
Keval Kothari manages marketing, operations, and the full HubSpot setup at iNymbus. He had watched buyers shift toward AI-first research and understood what it meant for a company competing in a category dominated by a few well-known names.
iNymbus was already using Semrush to track keyword rankings and domain authority, and those signals pointed in the right direction. Semrush could not show where iNymbus appeared when someone asked an answer engine for a recommendation. There was no visibility into which queries were surfacing competitors, no map of the content gaps leaving them out of AI-generated responses, and no system for turning that insight into a plan. The market for deduction management software was consolidating around vendors that answer engines trusted, and iNymbus had no structured way to know where they stood.
A Developer Caught in Reporting
Leadership at iNymbus needed regular reports on marketing and sales performance, and every request landed on Keval. Building a report meant figuring out which fields to pull, which chart type to use, how to configure the axes, and how to produce something a leadership team could read in a meeting. For a lean team with marketing, sales, and operations all running out of HubSpot, that overhead added up fast. Hours that should have gone to strategy were going to report configuration instead.
The Solution
The Suppliers iNymbus Serves Needed Them to Show Up
When a finance manager at a mid-size CPG company types "best deduction management software" into ChatGPT, the answer reflects which vendors have content that answer engines cite, trust, and surface consistently. iNymbus adopted HubSpot AEO to understand exactly where they stood in those moments.
AEO gave Keval's team a view Semrush could not provide: the specific queries their prospects were asking across answer engines, a running account of where iNymbus appeared and where they did not, and a prioritized list of content opportunities built from actual user search behavior. The team moved from guessing what to write next to working from a queue of topics that search data had already validated.
A Content Calendar Built on What Buyers Are Actually Asking
The AEO recommendations fed directly into iNymbus's content planning. Keval's team reviewed the suggestions, identified which prompt groups represented the highest-value entry points for their category, and assigned blogs and articles to match. The goal was content that answered the questions customers were asking answer engines so that the next time a supplier searched for deduction management help, iNymbus would appear in the answer.
AEO also surfaced opportunities the team had not considered: query clusters where iNymbus had a strong product story but no published content, and citation sources appearing repeatedly in competitive results. The platform connected visibility measurement to content action in a way that made the work feel less like monitoring and more like running a channel with real accountability.
Ask Once, Get the Report
Alongside the AEO work, iNymbus started relying on HubSpot's Breeze Assistant for the reporting that had been absorbing developer time. Keval describes the old process: deciding which fields to put on each axis, working through aggregation options, choosing the right chart type, building something readable for a leadership meeting. Breeze Assistant replaced that sequence with a prompt. He describes what the report needs to show, Breeze Assistant generates it from the actual CRM data already in HubSpot, and the result goes straight into the dashboard.
Because Breeze Assistant runs on the same customer and deal data powering every part of iNymbus's HubSpot setup, every report starts from actual pipeline history, campaign performance, and contact activity. There is no separate data pull, no reformatting, no switching between tools. The team gets leadership-ready reports on demand, and Keval gets the hours back to run campaigns and manage sequences.
The Transformation
A Lean Team That Competes Like a Larger One
The clients iNymbus serves are small-to-large-size suppliers competing against retailer systems running at machine speed. iNymbus wins for those clients by deploying automation that matches what the retailers are running. Inside their own business, the same logic now applies.
AEO turned a fragmented content guessing game into a system with inputs, outputs, and clear ownership. Keval's team reviews recommendations, assigns articles, publishes content tied to the prompts driving the most relevant traffic, and tracks visibility movement on those prompts through the AEO dashboard. The work that used to start with "what should we write about?" now starts with a ranked list of where iNymbus is underrepresented and what it would take to close the gap.
Showing Up Where Suppliers Are Searching
iNymbus is already ranking on answer engines as a top deduction management software recommendation, and AEO is extending that position. For a company whose value proposition centers on giving CPG suppliers a smarter alternative to manual processes, appearing as the recommended answer when those suppliers search is how the pipeline starts. Prospects who arrive having already seen iNymbus named by ChatGPT or Gemini carry a different level of conviction than those who land through a paid keyword. The first conversation starts further along.
Ten to Twelve Hours Back Every Week
Breeze Assistant has recovered approximately 10 to 12 hours of developer and operations time per week that previously went to report building. On a small team running three business functions from a single platform, that shift matters. Leadership gets the visibility they need. Keval and his team get the time back to build and run the programs that grow the business.
Keval describes the change in straightforward terms: a few months ago he was deciding which field to put on which axis and which chart type to use. Now he writes a prompt and the report is ready. "With HubSpot AEO and Breeze, we went from manually tracking rankings and building reports by hand to having a content system that tells us exactly where to show up and a reporting tool that does the work for us. It saves us 10 to 12 hours a week and it's changed what our team can actually get done."
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