No More
AI agents finally work. Here's how to put them to work safely, starting Monday.
Jeff Knauss · CEO & Co-Founder, Arcovo AI
1980
AT&T commissions a forecast: how many Americans will carry a cell phone by the year 2000?
Forecast 0
A $4,000 brick with a 30-minute battery, when there's already a phone on the kitchen wall. A niche product.
Actual 0
Off by more than 100×
AT&T believes it and passes. Its own Bell Labs invented cellular.
A cable-TV entrepreneur, Craig McCaw, buys up licenses and builds the biggest cell network in America.
1994: AT&T pays $11.5 billion to buy McCaw and get back into the market it said would never happen.
$4,000
2 lbs · 30 min battery
Friday night, 2004
Friday night, today
Where this is going
Headless software.
Today: the phone on the kitchen wall Walk to the system. Click. Filter. Export. Repeat.
0 clicks
Accounts Filter Deals Notes Email search Calendar Export CSV Pivot table Ask Sharon
Tomorrow: the phone in your pocket Ask. The agent goes and gets it.
Where do we stand with Acme, and when do we meet next?
They signed Tuesday and kick off Monday. Their COO already wants a second AI employee in Q1. Next meeting: Thursday at 2:00.
Agents become the interface. Your data is the value.
Anthropic S-1 filing
This is what demand looks like.
One quarter of 2026 = 2.5× all of 2025
Q2 '26 vs Q2 '25: ~15×
All of 2025: $4.6B → first half of 2026: $16.3B
Who's paying? Businesses.
0 %
of revenue is usage-based: companies running AI inside their workflows , not people chatting.
Anthropic S-1, H1 2026
1,500
up from 1,500 in December
companies spending $100K+ a year . That's 8× in nine months.
Anthropic S-1
10%
88% of companies use AI
Only about 1 in 10 have made it pay off at scale. We are still early.
Deloitte, State of AI in the Enterprise 2026
The companies that figured it out are spending like it's an arms race. Everyone else is still deciding. That gap is your window.
PART ONE
Accounts Payable.
One invoice. Two eras.
Accounts payable
The life of one vendor invoice.
Northside Packaging Co. Syracuse, NY
INVOICE
Invoice #4471 PO-2210 Net 30
Item Qty Price Corrugated boxes, 18×18 100 $4.20 Pallet wrap 12 $31.00 Freight 1 $185.00
Total $977.00
1 Vendor emails a PDF to ap@
2 The AP clerk checks it against the PO
3 Doesn't match? Emails the vendor and waits
4 Chases an approver
5 Enters it into QuickBooks
6 Schedules the payment and files it
Every company in this room does this hundreds of times a month.
2015 · Robotic process automation
Enter the bot.
Open emailInbox ap@
Read fieldsOCR + a template for every vendor
Match the POExact match only
Enter in QuickBooksField by field
Queue the paymentReady to pay
Works 24/7Never sleeps
Never makes a typoSame keystrokes every time
Paid for itselfAs long as nothing changed
RPA started the automation age. But it could only follow orders.
Then reality showed up.
Monday
The vendor redesigns their invoice
Total moved from the bottom-right to the top-left
BOT STOPPED
Tuesday
PO says 100 boxes. 96 shipped.
100 ≠ 96
KICKED TO A HUMAN
Wednesday
The invoice arrives as a phone photo
IMG_4471.jpg (sideways, with a thumb)
BOT STOPPED
Thursday
A handwritten note: "Net 45 per Dave"
Net 45 per Dave
IGNORED IT
Friday
"Please update our bank details"
New routing #, sent from a look-alike domain
CAN'T SPOT FRAUD
Every exception = a ticket, a developer and a restart.
Same invoice. Now with an AI agent.
Monday
New invoice layout
Agent Reads any format. No template needed.
Tuesday
100 ordered, 96 shipped
Agent Approves 96, holds 4, drafts the email to the vendor.
Wednesday
Phone photo
Agent Reads the photo like it's a PDF.
Thursday
"Net 45 per Dave"
Agent Checks the contract, flags the change, routes to a human.
Friday
"Update our bank details"
Agent Flags possible fraud. Requires a callback before anything changes.
When it isn't sure, it asks a person.
Why everyone is talking about this now.
RPA (2015) AI agent (today) How it works Follows steps Understands the goal When something changes Breaks Adapts When it's stuck Needs a developer Escalates, with a reason
RPA could only automate perfect processes. There aren't many.Agents handle the messy majority.
Same pattern. Everywhere.
Sales Inbound lead response Every lead answered in minutes, not days
Sales Lead research & enrichment Prospects researched before the first call
Sales Proposal generation Deal context in, ready-to-send proposal out
Sales Quotes & estimates Built from your line items, job history and vendor pricing
Clients Client onboarding Contract signed, systems populated, kickoff ready
Clients Client reporting Updates assembled from your systems, on your cadence
Support Ticket triage Every request sorted, routed and started
People Employee onboarding HR, IT and facilities coordinated; certifications tracked
Finance AP & AR Invoices processed, overdue accounts chased, finance approves
Finance Invoicing Billing reconciled, invoices drafted for review
Finance Job costing & profitability What every job actually made
Leadership Data visualization CRM, ERP and spreadsheets turned into live dashboards
Why it matters
One deal. Two salespeople.
Day 0
Lead to onboarded · illustrative
Without AI Onboarded · Day 45
Speed Consistency Time to value Time to revenue
The customer gets more, faster. The salesperson gets to focus on the relationship.
PART TWO
Data is the food
"My data isn't ready."
A messy pantry is fine. Spoiled food is not.
✓ Messy is fine
Files in the wrong folder No naming convention 14 versions of the price list Answers buried in email threads ✗ Wrong is not
Prices that are out of date Records that were never entered Contacts who left in 2019 Two systems that disagree
Agents don't need tidy. They need it to exist , and they need it to be right.
Where does the data live?
YOUR ENVIRONMENT
Email
QuickBooks
PO system
Teams
Agent
⇄ Encrypted in transit
■ Encrypted at rest
⚿ Credentials in a vault, not a script
☰ Every action logged
✋ A human approves money
✗ Providers don't train on your data
The data stays home. The agent visits.
Treat an agent like a new hire.
New AP clerk AI agent Identity A login = Its own account, never a shared one Role Only what the job needs = Least privilege Training SOPs = Specific instructions Supervision A manager = Human approval on what matters Accountability A paper trail = Every action logged Offboarding Turn it off = Turn it off
Headlines: Agents running loose and causing chaos!
New York, 1945
Automatic elevators existed for decades.
Nobody would ride one without an operator.
Then the operators went on strike, and the city stalled.
So the industry designed trust in:
An emergency stop button An emergency phone A calm, recorded voice Today, an elevator operator would feel strange. Trust is designed.
▲ 12
Human in the loop
Agents do the work. Humans make the calls.
Let the agents take
The repetitive The mundane Data entry and matching Chasing and follow-ups First drafts Keep the humans on
The final decision Critical thinking Relationships Judgment on the exceptions Accountability
Agent prepares → Human decides → Agent executes
Lean into the uniquely human work. That's where your people win.
PART THREE
Three waysto work.
Most companies are picking one without realizing it.
1 · Point solutions 2 · Environmental AI 3 · Orchestration you own
Point solutions: one tool per problem.
× Solves the same problem for everyone, the same way
× Doesn't fit how you actually do the work
× 40 vendors with access to your data
Fast to start. Hard to scale.
1 · Point solutions 2 · Environmental AI 3 · Orchestration you own
Environmental AI: agents inside your software.
Microsoft Copilot Salesforce Agentforce HubSpot ✓ Works well if your data lives there
Inside your CRM
Lead follow-up agent
Quote builder agent
Renewal reminder agent
🔒 Their model your only option
Switch CRMs. Lose it all.
Problem 1
Your workflows live in their software. Change your CRM, ERP or project system and every workflow you built goes with it. Problem 2
You can't change the model. Models keep moving in price and quality. You're stuck with the one they picked, at the price they set.
1 · Point solutions 2 · Environmental AI 3 · Orchestration you own
Orchestration you own: agents working together.
Any model Claude GPT Gemini Open source ⇄ swap any time
Your orchestration platform
Agent Reads
→ Agent Checks
→ Agent Acts
= AI employee Your exact workflow
Any system CRM ERP Email Projects Files ⇄ change it, keep it all
✓ Built for your exact workflows , not plug and play
✓ Any model , so you can optimize your token costs
✓ Change your software, lose nothing
This is how we build at Arcovo.
PART FOUR
Arcovo runs on agents.
Everything I just told you to do, we did to ourselves first.
The connected brain.
ArcovoAI agents
Where do we stand with Northside Packaging, what's blocking their build, and when do we meet next?
Status: signed on Oct 21 and starting implementation. Their CFO called it "the easiest yes we've made this year" (kickoff call) .
Blocker: the build is waiting on their QuickBooks admin access, 3 days so far (Jira) .
Next meeting: Thursday, 2:00 PM. Their CFO accepted (calendar) .
Read.ai · 2 calls Email · 4 threads Jira · 1 ticket Calendar CRM
Arcovo OS: how we run the company. Live from HQ (sort of)
⚲ Ask anything ⌘K
Meetings
Critical Numbers
IMP Status Reports
Reporting
Revenue & AR
Forecast Accuracy
Client Work
Consultations
Implementations
Live Clients
Accounts
Jeff Knauss
Critical Numbers Meeting Agenda IMP Status Critical Numbers Issues
Critical number 1
✱ Median Project Cycle Time Ahead of Target
Q4 new starts · weeks from kickoff
Vandelay Industries
3.2 wks Los Pollos Hermanos
2.9 wks
Critical number 2
✱ AI Employees Live in Q4 Comfortably On Track
Weekly Leadership & Ops Meeting Agenda IMP Status Reports Critical Numbers
Data refreshed this morning Synced from the CRM each morning.
✱ IMP Status Review · 4,812 of 4,812 active IMPs reported
Client ASM Stage Status Sentiment Go-live Days AI Emps Live MRR Dunder Mifflin Paper Co.Paper Sales & Beet Farm Ops Pam Live Green Ecstatic Oct 3 41 Ahead 12/12 $41,700 Acme CorpAnvil & Rocket Skate Logistics Wile E. Live Green Ecstatic Oct 7 38 Ahead 9/9 $38,250 Stark IndustriesSuit Inventory & AP Pepper Live Green Ecstatic Oct 9 36 Ahead 21/21 $96,000 Vandelay IndustriesImporting / Exporting George Live Green Ecstatic Oct 12 33 Ahead 4/4 $12,400 InitechTPS Report Automation Milton Live Green Ecstatic Oct 14 30 Ahead 7/7 $22,050 Los Pollos HermanosFranchise Operations Gus Live Green Ecstatic Oct 15 29 Ahead 11/11 $33,800 Bluth CompanyBanana Stand Finance Michael Live Green Ecstatic Oct 18 27 Ahead 3/3 $9,900 Cyberdyne SystemsDefinitely Not Skynet S. Connor Live Green Suspiciously Happy Oct 21 24 Ahead 800/800 $1,000,000
Revenue & AR Overview Forecast Trends Receivables
This Month · 3 Days Left
On pace to beat goal with 3 days left.
Monthly Recurring Revenue
Churned MRR (this quarter)
$0 Top-client share of MRR
Dunder Mifflin 0.0005%
Live Clients Clients Risks 0 Growth Snapshots
✱ Red Accounts · 0 No live client is rated red.
✱ Check-ins Overdue · 0 Every client has heard from us this week.
Consultations AWCs Actions Lists
0
Total open AWCs (it's over 9,000)
Deal BDM Signed Days in Next step AWC: Gringotts Bank JK Oct 26 2 Deep dive with the goblins AWC: Sterling Cooper JK Oct 25 3 Blueprint presentation AWC: Hooli JK Oct 24 4 Kickoff (they want to "make the world a better place")
⚲
Three clients mentioned Q1 expansion budget on calls this month:
• Acme Corp (Oct 14): wants two more AI employees "for the roadrunner project."
• Stark Industries (Oct 19): asked about AP for all 14 subsidiaries.
• Dunder Mifflin (Oct 22): Michael wants a "World's Best Boss" agent. We advised against it.
Drafted follow-up emails for all three. Ready for your review.
Read.ai · 3 calls CRM · 3 deals Email · 5 threads Drafts · 3
Illustrative demo · fictional data
What the brain does for us. Every day.
1
Discovery follow-ups Drafted from the call transcript, in my voice, within the hour.
After every call
2
Kickoff emails Drafted the moment a client pays, built from what they told us.
On payment
3
Cash forecast 13 weeks out, rebuilt from the books and emailed to leadership.
Mon & Fri
4
Deal intelligence Who they are, what they've said, what to ask, before every discovery call.
Before every call
5
Support tickets From the client's email to shipped code. In minutes.
Next slide →
Support tickets
Days or weeks → minutes.
01 · CLIENT Emails support "Can the weekly report include Region 4?"
02 · AGENT Reads the request Understands what's being asked
03 · AGENT Pulls the project history Jira tickets, call transcripts
04 · AGENT Reads the code Finds where the change goes
05 · AGENT Makes the change Opens it for review
06 · HUMAN ENGINEER Reviews & approves Nothing ships without this
07 · AGENT Ships it Change goes live
08 · AGENT Emails the client "Done. Region 4 is in this week's report."
Before Days or weeks
Now Minutes. With a human in the loop.
Client story · scDataCom · The problem
Salespeople buried in admin.
A security systems integrator selling to federal and commercial customers.
A salesperson's day
Admin & data entrymore than half
Selling
Hunting bids Searching SAM.gov for federal opportunities by hand
Logging deals Typing every opportunity and email into the CRM
Building quotes Pulling specs out of bid documents line by line
Writing proposals About 8 hours for every federal proposal
Client story · scDataCom · The solution
Five AI employees joined the sales team.
Samantha Finds federal bids
Dexter Pulls data from documents
Quinn Builds the quote
Preston Drafts the proposal
Olivia Keeps every deal updated
Federal opportunities found and logged by AI
0
≈ 800 hours of manual searching. Twenty work-weeks.
3.5 hrs
back in every salesperson's day
$6,000+
a month in staff time saved
+20%
more qualified opportunities
25+
companies they've referred to us
“
I was a bit of an AI naysayer, and then Arcovo just blew my socks off.
Kathleen Ford, CEO, scDataCom
Client story · Ollivier · The problem
Their clients were flying blind.
Ollivier provides security guards and runs security systems for businesses.
Guards
Patrol logs
Shift reports
Incident write-ups
×
Systems too old to talk to each other Security systems
Cameras
Access control
Alarms
"Were all my patrols covered last night?"
→
Someone has to go dig through the logs .
Client story · Ollivier · The solution
One screen for guards and security systems.
Day 1 Vision on a call
Day 30 Live demo at their trade show
Day 90 In clients' hands
✓ Every milestone hit
1 Pulls guard and security-system data into one secure client portal
2 Clients ask questions in plain English and get answers in seconds
3 Maps patrol coverage and flags the gaps
4 Writes every client's monthly report
Anything sensitive goes to an Ollivier staff member.
Client security portal
98% Patrol coverage
142/142 Cameras online
3 Incidents this week
Were all patrols covered last night?
14 of 14 rounds completed. One late check at Gate B, 11:52 PM.
Illustrative
“
This is by far the best experience I've ever had with a technology deployment.
Louis Boulgarides, President & CEO, Ollivier
Client story · Precision Walls / AES · The problem
Every bid started from scratch.
AES, Precision Walls' exterior division, bids the outside of commercial buildings.
283
pages in one drawing set
By hand, for every bid
1 Read every page to find what's in scope
2 Measure square footage and linear feet
3 Price materials across three suppliers' spreadsheets
4 Estimate labor and build the proposal
20–30 hrs
of estimator time per bid
2–3 days
to get one proposal out the door
Client story · Precision Walls / AES · The solution
An AI estimator that does the first draft.
283 → 283 pages
It reads the whole set and pulls the 7 pages that matter .
1 Finds the scope and flags every in-scope product
2 Measures square footage and linear feet, by area
3 Estimates the labor and prices materials across three suppliers
4 Drafts the proposal PDF
★ In testing, its labor estimate came within about 5% of their own estimator's
✓ The estimator reviews and approves every stage
Estimators stop starting from scratch. They review, approve and bid more jobs with the same team.
Start Monday.
1 Pick one painful, repetitive process. Getting the right use case is critical to success and return on investment.
2 Write down where its data lives. And who owns access to it.
3 Pilot it read-only, with a human approving. Measure it for 30 days.
arcovo.ai · jeff@arcovo.ai
In 1980, nobody needed a phone in their pocket.Today, nobody needs to click 200 times.
No more waiting.
Jeff Knauss · CEO & Co-Founder, Arcovo AI · jeff@arcovo.ai · arcovo.ai
Thank you
Give feedback
Scan the QR code, or go to
talk.ac/arcovoai
and enter this code when prompted
CEO1
Scan with your phone camera
Powered by Talkadot
