Notes on AI, from the field.
Thinking from the AI Force team on the home services industry and what it takes to make enterprise AI work in production.
One CRM every AI Force product runs on
AI Sales, AI Marketing, and AI Customer Service could each have shipped with their own data store. Here's why we built one CRM underneath all three instead.
One AI agent, every channel: rethinking omnichannel support
Chat, voice, SMS, email, and video usually mean five separate tools and five separate histories. Here's why AI Customer Service treats them as one conversation instead.
Read moreProduct · August 22, 2026AI Sales, built on the CRM you already run
We didn't want reps re-entering data into yet another system. Here's why AI Sales mirrors your CRM instead of replacing it.
Read morePerspective · August 21, 2026Why AI Customer Service has a human inbox, not just an AI one
An AI agent that never admits it's stuck is a liability, not a feature. Here's why we built a real inbox for the moments it should hand off.
Read moreProduct · August 20, 2026Why marketing teams are handing brand voice to AI
AI-generated content is only useful if it sounds like your brand. Here's how AI Marketing keeps every draft on-voice.
Read morePerspective · August 19, 2026Multi-tenancy that's enforced, not assumed
A tenant filter that only lives in the front end is one bug away from a data leak. Here's why AI Force CRM checks organization scope on every request instead.
Read moreProduct · July 20, 2026Grounding support answers in your own knowledge base
A model's training data isn't the same as your product's actual documentation. Here's how AI Customer Service keeps answers grounded in what you actually publish.
Read moreIndustry · July 14, 2026Why home services companies are turning to AI
Quoting, contracting, and getting paid are still manual in most of the home services industry. Here's where AI actually removes friction.
Read morePerspective · July 5, 2026Scoring you can actually explain
A black-box model can't always tell you why a lead scored the way it did. Here's why AI Force CRM's scoring is built to be read, not just trusted.
Read morePerspective · June 25, 2026AI content assistance vs. AI content automation: where we draw the line
Generating content and publishing it are two different decisions. Here's why AI Marketing keeps a person in between.
Read moreProduct · May 6, 2026From room scan to signed contract: inside HomePro's AI pipeline
A look at how HomePro turns a LiDAR scan into a floorplan, an estimate, and a ready-to-sign contract.
Read moreProduct · April 10, 2026Forecasting with AI commentary: numbers plus a narrative
A pipeline rollup tells you what changed. It doesn't tell you why. Here's how AI Sales closes that gap.
Read morePerspective · March 18, 2026What we look for before recommending an AI solution
Not every workflow needs AI. Here's how we decide where it actually helps a client, and where it doesn't.
Read moreIndustry · February 15, 2026One campaign, five channels: the case for AI-native scheduling
Marketing teams still adapt and post the same campaign to every channel by hand. Here's what changes when scheduling is AI-native.
Read moreIndustry · January 22, 2026LiDAR on every phone: a turning point for home estimating
Depth sensors that used to require dedicated hardware now ship in everyday phones and tablets — and that changes what's possible for estimating.
Read morePerspective · January 5, 2026Why we gave AI Sales a shared memory, not just more features
Outreach, forecasting, and coaching were built as separate modules first. Here's why we connected them with one shared timeline instead of leaving them siloed.
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