Real businesses. Real work made visible.
Three service businesses handed GraniteAI their work. Below is the record it captured, the system it built from that record, and the verified result, where a business has one to share.
The engine that fills those feeds is below too. Sourced market data you can sample for free.
What these businesses got back.
8 hours a week
Aron Compton Insurance
Aron keeps a full feed without lifting a finger. His words are in the card below.
A feed that fills daily
Olera Cleaning
Olera keeps posting while she runs the jobs. Her words are in the card below.
Completed jobs, turned into public proof
Alpine Built
Photos become before, progress, and after stories in the business voice. The photo-to-post pipeline is a shipped capability.
Alpine Built
Problem
Good completed work was not becoming durable public proof.
Context captured
Services, territory, brand, project types, job photos, and publishing rules.
System
Send job photos and they're sorted into before, progress, and after stories, written in the business's voice, quality-checked, and published automatically.
Verified result
No outcome published yet. The photo to reviewed post pipeline above is a shipped Mica capability.
Olera Cleaning
Real published postProblem
Commercial-cleaning visibility depended on owner effort.
Context captured
Facility types, cleaning scopes, proof standards, recurring services, and brand voice.
System
Consistent, reviewed content based on the actual service model, published daily.
Verified result
“My priority is getting the job done at the highest quality - and this means I don't always have time to think about what to write in a social media post. Mica took this off of my plate, my feed fills - all while I focus on what I do best! This is a game changer, and I would recommend it to any service business.”
Olera Cleaning
Aron Compton Insurance
Real published postProblem
Local education and trust needed a reliable cadence.
Context captured
Products, life events, local market, compliance boundaries, and educational themes.
System
Reviewed local insurance content grounded in agency context, compliance-aware, published on a reliable cadence.
Verified result
“I know I need to post daily, but my customers come first so I don't always have time. Mica ensures my feed stays full without my lifting a finger. When I do take pics, the system automatically writes captions, hashtags, and ensures compliance with my brand! Mica has saved me 8 hours a week!”
Aron Compton, Aron Compton Insurance
These feeds are published by Mica. See what it would post for your trade →
Your business, written as a file your AI can read.
Give us your website. We read it and build a business context kit: 87 canonical values that describe how you operate, who buys from you, and how you sound. We email it to you. Load it into Claude or ChatGPT, and every answer is about your business instead of a generic one. Free.
| Section | What it captures | Typical fields |
|---|---|---|
| Identity | Who you are | 12 |
| Operations | How you run | 8 |
| Offering | What you sell | 16 |
| Customers | Who buys from you | 12 |
| Voice | How you sound in writing | 17 |
| Proof | What makes you credible | 9 |
| Presence | Where you show up | 6 |
| Market | Your federal NAICS classification | 7 |
Typical field counts. What we look for in each section. Your kit reflects what your site actually says. 87 canonical values in total.
The kit is a point-in-time record built from your site. It does not include live market data. That is the engine's job, below.
A signal is a number, its source, and what to test.
Mica Intelligence turns the verified foundation into signals as your market moves. Below is the format: one number, its source, and a decision worth testing. This example draws from the public market store, not a specific account.
The county recorded 3 hail and 8 thunderstorm-wind events. Rockingham County, New Hampshire.
- What it could mean
- Recent storm history is one signal worth testing for timing. It does not by itself prove demand.
- Decision to test
- Test storm-timed follow-up and faster quotes in older-housing areas before cutting price.
- Measure
- Compare close rate and margin by timing and area cohort.
Sample format. One signal, drawn from verified public data. Not a client result.
A real number, where it came from, and when it was true.
Every fact the Mica Intelligence Engine serves keeps five things. Source, date, place, industry match, and the limit on how far it should be read. No hand-picked anecdotes.
Roofing establishments rose from 17 to 21.
County business applications rose from 4,316 to 4,767.
The county recorded 3 hail and 8 thunderstorm-wind events.
ZCTA 03801 has a median structure year built of 1959, plus or minus 3 years.
Worked example: Owner-led roofing contractor, Rockingham County, New Hampshire.
1,546,037
verified observations. Live database read-back, August 6, 2026.
Across 183 market series and 16 public dataset families.
Census CBP
1,212,021
Census BFS
126,996
Census ACS
67,236
FEMA NRI
59,736
NOAA Storm Events
36,848
Census Building Permits
22,122
Census Population Estimates
4,990
FEMA NFIP Flood Insurance
4,038
BLS Producer Price Index
3,294
EIA Short-Term Energy Outlook
2,887
BLS Consumer Price Index
2,316
HMDA Mortgage Originations
1,470
FEMA Disaster Declarations
1,256
FRED Monthly State Retail Sales
528
IRS SOI Migration
240
NH Professional Licensing
59
The examples above describe Rockingham County, New Hampshire, where the foundation is deepest today. Coverage is deepest around the regions we already serve. We do not claim national depth.
The same discipline runs underneath every local system.
Enterprise clients stay anonymous by contract. The scale is real.
AI agents run operational processes for a leading cloud computing platform. Work that once needed manual effort now runs at enterprise scale.
Their team no longer keys data into Salesforce. A custom AI system captures it and moves the workflow on its own.
Under contract to hand entire back-office operations to AI systems: millions of transactions, zero downtime.
Deal registration, from a chat
Partners of a major enterprise software company register deals from inside the AI assistant they already use. The agent reads the facts from their work context, asks for anything missing, validates the registration, and files it in Salesforce once the partner confirms.
A partner manager's copilot
Partner managers at the same company ask plain questions about pipeline, co-sell overlap, and deal registration performance. The agent answers from live Salesforce data and recommends the next action, with the right partner contact attached.
Start with your own data.
Give us your website. We build your free business context kit and email it to you. Load it into Claude or ChatGPT and see the difference before you pay anything.