Paloma Thinks Your Post-Sales CRM Is a Mess and Honestly It Probably Is

The Macro: CRM Stops Caring About Your Customer the Moment They Sign

The CRM industry is worth something like $80 billion. Salesforce alone does $35 billion in annual revenue. HubSpot, Pipedrive, Close, Attio. The market is mature, well-funded, and thoroughly explored. Except for one enormous blind spot.

Almost all of that CRM investment is pointed at pre-sales. Tracking leads, managing pipelines, forecasting deals. The entire architecture of modern CRM was designed to answer one question: will this prospect become a customer? Once they do, the system largely stops being useful.

Post-sales is where the money actually lives. For SaaS companies with usage-based pricing, the initial contract is just the starting point. Expansion revenue, upsells, renewals, consumption tracking, contract amendments. This is where customer lifetime value gets determined. And for most companies, this critical function runs on a combination of Salesforce custom objects that nobody maintains, spreadsheets that are always out of date, and the institutional memory of whoever has been on the account longest.

Gainsight tried to solve this and built a significant business doing it. Totango and ChurnZero are in the space. But these are customer success platforms, not CRMs. They bolt on top of Salesforce and try to surface health scores and playbooks. The underlying data architecture is still fragmented. Contracts live in one system. Billing lives in another. Product usage lives in a third. Customer communications live in email. Nobody has a unified view.

The problem gets worse with complex pricing. If you are selling per-seat, it is relatively simple. If you are selling consumption-based, tiered, or hybrid pricing, tracking what a customer is actually using versus what they are paying for versus what their contract says becomes a genuinely hard data problem.

The Micro: The Deel Team That Saw Post-Sales Break at Scale

Paloma is building an AI-native CRM specifically for post-sales operations. The core idea is unifying contracts, service consumption, and customer relationship context into a single system. From there, it surfaces upsell and churn signals, automates billing workflows for complex pricing, and integrates with existing CRM and billing systems.

The founding team is the real story here. Nazli Danis is CEO. She was the first product hire at Deel and led the Employer of Record division as it scaled from almost nothing to a major revenue line. Alex Avnit is CRO. He ran Deel’s EOR business unit and brings a quantitative, data science background. Kaiwen Song is CTO. He built Deel’s billing and payment infrastructure from scratch and was there from Series B through the $12 billion Series E valuation.

All three of them watched post-sales operations break at Deel’s scale. They saw firsthand what happens when contract complexity outgrows the tools designed to manage it. That is about as strong a founding insight as you can get. They did not read a market report and decide to build a CRM. They lived through the pain at one of the fastest-scaling companies of the last decade.

They are a three-person team in San Francisco, part of Y Combinator’s Summer 2025 batch. The product integrates with existing CRM and billing systems rather than trying to replace them entirely. That is the right approach. Nobody is ripping out Salesforce for a startup. But plenty of companies would layer something on top that actually makes post-sales data coherent.

The AI-native piece means the system can process contracts, identify relevant clauses, track consumption against thresholds, and generate alerts when an account is trending toward churn or expansion. This is the kind of work that customer success managers currently do manually, and they do it badly because the data is scattered across six different tools.

The Verdict

I think Paloma is going after a market that is genuinely underserved. Post-sales CRM is not a sexy category, but it is an important one. Every SaaS company with usage-based pricing knows their post-sales data is a mess. Most have accepted it as an unsolvable problem. If Paloma can actually unify the data layer and surface actionable signals, the value proposition sells itself.

The risk is the integration burden. Post-sales data lives in billing systems, product analytics, support tickets, contracts, and CRM records. Connecting all of those sources is a significant technical challenge, and every customer’s stack is different. Gainsight has been at this for over a decade and still struggles with data quality. Paloma needs to prove it can get clean data faster than existing solutions.

In thirty days, I want to see how many design partners they have and whether the data unification actually works in practice. In sixty days, I want to know if the churn and upsell signals are accurate enough that customer success teams trust them. In ninety days, the question is whether this becomes the system of record for post-sales or just another dashboard that people check once a week. The Deel pedigree gives them credibility. Now they need to prove the product delivers.