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Most “AI CRMs” are just old databases with a ChatGPT button. You still type everything in, or the data goes stale in a week. Newly launched Lightfield (Lightfield) flips that: it treats emails, calls, and meetings as the source of truth. The structure assembles itself around the raw conversations....

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Rohan Paul

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22,939 Aufrufe • vor 9 Monaten •via X (Twitter)

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1/ The end of manual CRMs Most CRMs fail because they force manual typing, so data rots the moment a meeting ends -yet CRM’s core job is the vital, grueling task of logging every customer touchpoint, and in the AI era this human bottleneck turns dynamic relationships into a slow, error-filled slog that no team can sustain. Lightfield fixes that by auto-capturing all interactions—calls, emails, Slack, notes - so it’s the first CRM that truly knows your relationships as well as you do.
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1/ The end of manual CRMs Most CRMs fail because they force manual typing, so data rots the moment a meeting ends -yet CRM’s core job is the vital, grueling task of logging every customer touchpoint, and in the AI era this human bottleneck turns dynamic relationships into a slow, error-filled slog that no team can sustain. Lightfield fixes that by auto-capturing all interactions—calls, emails, Slack, notes - so it’s the first CRM that truly knows your relationships as well as you do.

Chubby♨️

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Today we're announcing Lightfield's $47M Series A led by a16z to reimagine CRM as a world model of a business. For agents to do customer-facing work, they need to understand how your business actually works. Salesforce wasn't designed for this. It was built 20+ years ago for humans to update records. Layer agentic processes on top and you get low quality output, because the underlying data is incomplete and lacks the structure agents need. Lightfield updates itself from every interaction, forming a trustworthy model of your business for people and agents. Since launching last November, 5,000+ companies have signed up - and we're ripping out legacy CRM at mature organizations with hundreds of users. Companies on Lightfield grow faster than their competitors. It finds prospects that look like your best customers and books meetings with them. It captures commitments from every conversation and automates follow-ups. It diagnoses weaknesses in your funnel and learns from your best sellers to codify what works. The companies of the future will run on a business world model, not a Salesforce-era database. Our mission is to put that capability in the hands of every employee, and every agent, at every company.
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Today we're announcing Lightfield's $47M Series A led by a16z to reimagine CRM as a world model of a business. For agents to do customer-facing work, they need to understand how your business actually works. Salesforce wasn't designed for this. It was built 20+ years ago for humans to update records. Layer agentic processes on top and you get low quality output, because the underlying data is incomplete and lacks the structure agents need. Lightfield updates itself from every interaction, forming a trustworthy model of your business for people and agents. Since launching last November, 5,000+ companies have signed up - and we're ripping out legacy CRM at mature organizations with hundreds of users. Companies on Lightfield grow faster than their competitors. It finds prospects that look like your best customers and books meetings with them. It captures commitments from every conversation and automates follow-ups. It diagnoses weaknesses in your funnel and learns from your best sellers to codify what works. The companies of the future will run on a business world model, not a Salesforce-era database. Our mission is to put that capability in the hands of every employee, and every agent, at every company.

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ChatGPT connecting to external data sources offers a glimpse into what AI interoperability looks like. Ask any question in ChatGPT and it can now pull data from Box. The future of AI is AI Agents that can access your systems and data to complete any task for you.
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ChatGPT connecting to external data sources offers a glimpse into what AI interoperability looks like. Ask any question in ChatGPT and it can now pull data from Box. The future of AI is AI Agents that can access your systems and data to complete any task for you.

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1/ My Co-founder Peter had 6 active negotiations, weeks of calls and emails and genuinely had no idea who actually mattered in any of them. Then, Lightfield just dropped its custom 'Skills & Knowledge' to their CRM. A game changer! We built one right away to map out all these client relationships. What we realized was we had a mess. But now, instead of clicking through a million tabs in a live meeting, Lightfield did the work. The key thing: every email, call, and interaction we had with each client was automatically captured. These skills always run in the freshest context for every client relationship. It doesn't rely on any one team member, and the data is always fresh, never stale. A 🧵:
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1/ My Co-founder Peter had 6 active negotiations, weeks of calls and emails and genuinely had no idea who actually mattered in any of them. Then, Lightfield just dropped its custom 'Skills & Knowledge' to their CRM. A game changer! We built one right away to map out all these client relationships. What we realized was we had a mess. But now, instead of clicking through a million tabs in a live meeting, Lightfield did the work. The key thing: every email, call, and interaction we had with each client was automatically captured. These skills always run in the freshest context for every client relationship. It doesn't rely on any one team member, and the data is always fresh, never stale. A 🧵:

Chubby♨️

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startups buy salesforce or hubspot by default because that's just what you do when you scale. the problem is those systems were built for reps manually typing notes. slapping ai agents on top of subjective, incomplete data is a bottleneck. lightfield actually rebuilt the crm for the agent era. full api and mcp access turns it into infrastructure. 5,000+ companies already moved. i've been working with the lightfield team, and their $47m series a is pure signal. opinions are mine.
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startups buy salesforce or hubspot by default because that's just what you do when you scale. the problem is those systems were built for reps manually typing notes. slapping ai agents on top of subjective, incomplete data is a bottleneck. lightfield actually rebuilt the crm for the agent era. full api and mcp access turns it into infrastructure. 5,000+ companies already moved. i've been working with the lightfield team, and their $47m series a is pure signal. opinions are mine.

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Everyone’s talking about the future of CRM. Let me tell you what it’s not: ❌ Fields & columns ❌ Manual data entry ❌ Clunky dashboards HubSpot’s CEO Yamini Rangan just admitted it on a recent podcast with The Logan Bartlett Show — traditional CRMs aren’t enough anymore. Most sales data is buried in unstructured data. The majority of that is in conversational data. And only one company has nailed capturing it. Fireflies is what an AI CRM of the future will look like. 🧵👇
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Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.

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