Lightfield
AI-native CRM that builds itself and does work for you
1.9K followers
AI-native CRM that builds itself and does work for you
1.9K followers
Lightfield reads your emails, meetings, and calls to build your CRM automatically. No manual data entry — ever. Connect your inbox, upload a spreadsheet or CSV from your old CRM, and everything is recreated in less than five minutes. Ask it anything in plain English: who needs follow-up, what objections keep coming up, how has our ICP shifted — answered from your actual conversations. Then put it to work to draft follow-ups, create board decks, build proposals, and more.
The schema-less approach is really smart — most CRMs force you into rigid data models that don't match how relationships actually evolve. I'm curious about two things:
How does Lightfield handle the "cold start" problem? When you first connect it, does it immediately start surfacing useful insights from existing email/Slack history, or does it need a few weeks of fresh interactions to become valuable?
For solo founders or small teams who wear multiple hats (sales, support, partnerships), does the AI differentiate between these relationship types automatically, or do you need to manually categorize them?
I run a content automation tool and the hardest part of building AI features is making them feel genuinely useful from day one, not just after months of training data. Would love to hear how you tackled that.
The auto-populate from inbox is the right way to solve the stale CRM problem ,changing behavior never works, so skipping the entry step entirely is the only real fix. What i'm curious about is scale: if a rep has 3+ years of email history with 200 threads per deal, is the context layer doing semantic chunking or brute-forcing full threads into retrieval? context window overflow is usually where these systems quietly degrade and nobody notices until the answers start getting weird. would love to know how you're handling that.
Really like the "builds itself" framing — we run into something similar with an AI moderation tool for Telegram communities where the bot has to learn each group's specific rules rather than apply universal logic. Curious: how do you handle the calibration period where the system is still learning the org's specific sales patterns vs the founder's prior assumptions about pipeline shape? Did your early users want more visibility into "here's what it's learning right now" or were they comfortable just trusting the output?
The "builds itself" framing is where CRMs have always fallen short — the value is in the relationship context, not the data structure, and getting salespeople to maintain data quality is a constant battle.
The use case of connecting an inbox and having it auto-populate pipeline from existing conversations is compelling for M&A and deal-flow contexts — that's exactly the kind of unstructured relationship data that lives in email threads and never makes it into Salesforce. I sell financial model templates on Eloquens and the relationship layer around deal sourcing has always been the gap no CRM solved well.
Does Lightfield handle the confidentiality sensitivity that comes with M&A deal flow, where counterparties are often sensitive about who knows what?
Game Changer!
After a couple days in Lightfield there is no going back to entering data into forms.
I dropped HubSpot about a month ago as it was way too complex for founder led sales but keeping track of stakeholders became an issue quickly. Now I spend 1/3 of my day chatting with Lightfield about my customers; their needs, segments etc and data is updated automatically - truly agentic. This is a great glimpse into what the future holds.
Migrated from HubSpot two months ago and the thing that surprised me most wasn't the AI, it was that I stopped dreading logging calls. It just does it. The deal revival workflow is genuinely useful, found 6 conversations from Q1 where a prospect had gone quiet after a positive signal I'd missed.
What I'd flag is the bulk email personalization is strong but occasionally overindexes on small details from a transcript that weren't actually meaningful like referencing someone's coffee preference from an offhand comment.
A "confidence threshold" setting for what the agent pulls into outreach would tighten that up. The weekly changelog cadence shows this team is actually shipping, not just announcing.
I was one of the very first people to sell Contact Managers and then Sales Force Automation products to salespeople in the late 80s. The salespeople hated it because of all the input it required... among other things.
CRM has come a long way since then. You've got a good start. Once you add Customer Service and Marketing you'll truly have an integrated AI-based CRM solution.
Lightfield
@jberkowitz - appreciate the kind words. I can relate, started my career as a salesperson and hated every minute I spent updating fields in SFDC. No more! Would love to hear what you think of the product if you get a chance to try it.