AI growth + operations for owner-led businesses
Find where your business is leaking money.
Then prove the fix.
Manual work. Disconnected systems. Missed follow-up. Spreadsheets holding critical processes together. InteractiveInfo finds the operational profit gaps worth fixing — then uses AI and custom software to prove the best solution before you make a major investment.
No chatbot pitch · No giant discovery project · Business case first
Founded 1994 · Three decades of custom business systems. We’ve delivered software for manufacturers, energy companies, real estate organizations, benefits administrators, and other operating businesses — long before anyone called these problems AI workflows.
Founded 1994 · Incorporated 1999
The mess
Nobody designed this. It accumulated.
A tool bought for one problem, a spreadsheet bridging two others, people carrying data between them by hand. It works until volume, turnover, or a customer question exposes it. Our job is the second picture.
Before / the mess
Nothing here is broken on its own. The cost is in the crossings: every line is a person, a re-type, or a thing that gets missed.
Does any of this sound familiar?
These aren’t IT annoyances. They’re profit gaps.
If more than one is true, money, time, or capacity is leaking out of the operation every week — and it rarely shows up as a line item anyone owns.
- A spreadsheet is quietly running a core part of the business
- PDFs arrive and someone re-types every field
- Approvals happen in email threads nobody can find
- Month-end reporting takes a week of manual assembly
- One person knows the process, and they're going on vacation
- Two systems hold the same customer, spelled differently
Proof before the big investment
Don’t take our word for it. Prove the best idea.
When the top opportunity suits rapid proof, we build enough of it to show how the work would actually run — representative data, outside your production systems. A working proof, not slides. Then you decide whether it deserves production investment.
Representative data only
The proof runs outside your live systems. Sanitized examples or a screen-share are enough to start.
Built for the people doing the work
It has to survive contact with the person who currently keeps the process alive by hand.
A proof, not production software
Production is a separate, scoped stage — with your IT team in the room.
Why the judgment matters
AI made us faster. It didn’t teach us how businesses work.
We’ve spent decades with owners, operations leaders, and the people doing the work — then turned what they described into production software: line-of-business applications, ERP-connected integrations, approval systems, consolidated reporting, quality and safety systems, field data capture.
The hard parts haven’t changed: knowing what to automate, what to leave human, and how to take a working prototype into software a company can run on for years.
Since 1994 · Incorporated 1999 · Today’s AI development speed
In practice
- We’ve translated business problems into working software since 1994.
- We’ve maintained our own systems for a decade or more, so we build things that can be handed over, changed, and lived with.
- We were solving ugly business processes long before anyone called them AI workflows.
Selected client work
We were solving ugly business processes long before anyone called them AI workflows.
Problem-first, as always: each of these started as a process someone inside the business was holding together by hand.
Motorola
Quality control
Moved a manual quality-control process off paper records into automated data collection, with notifications, analytics, and reporting built around it.
Praxair
Engineering-to-ERP workflow
An engineering-to-ERP workflow that transfers engineering designs into the ERP and manufacturing systems instead of people re-keying them between the two.
Anadarko Petroleum
Safety management
A safety management system covering safety meetings, incident tracking, training records, and compliance reporting.
Hines
Cost and cash-flow accounting
A cost and cash-flow accounting system tracking project budgets, revenue, expenses, and profitability.
Reliable Administration Services
Benefits administration
A benefits administration system supporting insurance plans, eligibility, enrollment, and billing.
Detail
We describe this work in scope and outcome terms on a call rather than publishing numbers we can’t substantiate in writing.
The AI Profit Diagnostic
Start with the business, not the technology.
The free AI Profit Scan is one conversation about where work is getting stuck. If something is worth pursuing, the AI Profit Diagnostic works through six zones of the business and ranks what is actually costing you the most.
- Acquisition
- Where demand is created — and where it quietly gets lost.
- Conversion
- Quotes, proposals, and follow-up that depend on memory.
- Fulfillment
- Delivering the work: hand-offs, rework, bottlenecks.
- Retention
- Repeat business, service recovery, accounts drifting away.
- Administration
- Duplicate entry, reconciliation, approvals in email.
- Strategy
- Whether leadership can see the business in time to act.
What you get out of it
- Your Top 3 profit gaps, ranked.
- An estimated economic impact for each — based on your numbers and our experience, not a guaranteed result.
- The root cause or operational constraint underneath each one.
- Whether the answer is buy, integrate, automate, build — or leave it alone.
- A recommended first move, not a twelve-month roadmap.
How it starts
The AI Profit Scan is free. If we uncover something worth pursuing, the full Profit Diagnostic is a separate fixed-fee engagement. No open-ended consulting meter.
Business case first · Integration project second
Why now
AI changed what is economical to automate.
Documents, email, and messy human input can now become usable business data, with people reviewing only the exceptions. And because development is dramatically faster, we can prove ideas that previously weren’t worth the time or cost.
What hasn’t changed: knowing which parts of a workflow should stay human, and how to hand over software a company can live with for a decade.
After the first fix
Where this can ultimately go.
First we fix the broken process. As systems and data become reliable, more of the routine work can run automatically across your ERP, accounting, CRM, and the tools your team already uses — inside rules you set, with approvals and an audit trail. Your people keep the judgment.
An event happens in the business, and the routine follow-through happens with it.
Turn operational mess into measurable value
Event
“Smith Co. paid their invoice.”
Agent
Matches the payment to the open invoice, checks the amount and any short-pay tolerance you've set, and reconciles it.
ERP
Invoice marked paid, credit hold released.
Accounting
Receipt recorded and reconciled to the bank feed.
CRM
Customer record and balance updated for whoever picks up the phone.
Downstream
Held order continues; collections follow-up cancelled.
Where a human steps in: A short-pay outside tolerance stops and routes to your controller with the evidence attached. Every action is logged, reversible, and bounded by rules you write.
Rules before autonomy
Agents act inside thresholds, policies, and reason codes your team writes down. Anything outside them escalates.
Everything is auditable
Each action records what happened, why, which policy applied, and what it touched. Reversible by design.
People keep the judgment
Exceptions, credit decisions, customer relationships — anything with real discretion stays with your team, surfaced faster.
After launch
We don’t disappear after launch.
Managed AI Operations keeps what we built worth having: running correctly, still earning its place, and improving as the business changes.
- Run
- Monitor + measure: are the systems and agents operating correctly, and still earning their place?
- Control
- Govern + train: what AI may do on its own, where a human approves, and how the team uses it.
- Improve
- Improve + expand: refine workflows and logic as reality changes, and find the next profit gap.
Your people keep the judgment. Your systems handle the routine work.
How this works
Four steps. No discovery theatre.
- 01
Profit Scan
A 20–30 minute conversation about where the business is constrained. Not a sales call.
- 02
Profit Diagnostic
We rank your Top 3 opportunities, name the root cause, and recommend the first move.
- 03
Proof + Implementation
Prove the best idea where practical, then scope and build production if it's justified.
- 04
Managed AI Operations
Monitor, measure, improve, govern, and expand what's running.
The next step
Start with the business problem.
Twenty to thirty minutes on where work is getting stuck, money is leaking, or growth is constrained. If there's nothing material there, we'll say so.