One operational data layer. Real-time signals. Governed decisions.
AIB2B connects the systems you already run, puts AI agents to work watching your finances, customers, people and compliance, and delivers one live dashboard and a Monday operating brief, with an experienced operator behind it.
No new software for your team. Your data stays in your accounts.
- financeTwo invoices totalling $18,400 are 30+ days overdue. Reminder drafted for approval.
- customerOnboarding tickets up 40% since the pricing page change.
- peopleOffboarding complete. Access removed from 9 of 9 tools.
- compliancePayroll remittance due Friday. Insurance renewal in 21 days.
Fragmented systems of record. Decisions bottlenecked at the founder.
Two years in, most founders run operations themselves: finance in one tool, sales in another, support in an inbox, hiring in a spreadsheet. Every decision starts with an hour of digging, and problems surface late.
of enterprise generative AI pilots showed no measurable profit and loss impact.
MIT, 2025
of AI initiatives delivered the return expected. Only 16% scaled across the company.
IBM CEO study, 2025
of leaders who cut jobs for AI now say it was the wrong call.
Orgvue, 2026
AI fails when it's bolted onto old work and people are removed before it's proven. We do the opposite: agents designed into the work, one workflow proven first, and people kept on every decision that needs judgment.
Integrate. Monitor. Surface. Decide. Operate.
System integration
We link the tools you already use. No migration, no new logins for your team.
Continuous monitoring
Agents monitor cash, revenue, customers, people, compliance and marketing.
Decision surfacing
One live dashboard and a Monday brief with what changed and what needs a decision.
Managed operations
We tune the agents, connect new tools and add new areas as you grow.
Bid Desk Florida: a multi-agent platform we built and operate in production
A bid platform for property managers: requests come in by email, agents write the scope and compare the bids, and a person approves every step. Same foundation, same security, same support model our clients get.
"Getting three good bids shouldn't take three weeks of calls. That's an operations problem, and operations problems are what we solve."
From the Bid Desk Florida build brief
Vertical operating systems for under-digitized industries, built and run by AIB2B
CondoReach Florida
Outreach and bid support for contractors serving condos and HOAs.
About the platformDeal Workbench
Acquisition diligence for professional-services firms, from NDA to lender-ready financing package.
About the platformEstatehood
White-label estate planning for law firms: wills, powers of attorney and living wills, with lawyer review.
About the platformMap your operating architecture in 30 minutes.
30 minutes. A one-page operations map in three business days. Free.
AI fractional COO: an operating layer deployed on your existing stack
For founder-led companies, about two years in and 10 to 50 people, with customers and revenue but no COO. We give you the visibility, rhythm and analysis a COO provides, at a fraction of the cost of a hire.
Six domain agents, each with a bounded scope
Finance & treasury agent
Cash, runway, overdue invoices and unusual spending.
Revenue intelligence agent
Pipeline, conversion, churn signals and top accounts.
Customer operations agent
Support themes, response times and at-risk customers.
People ops & access agent
Onboarding checklists and offboarding with access removed everywhere.
Governance, risk & compliance agent
Filings, renewals, access reviews and policy reminders.
Growth attribution agent
What's working by channel and what each customer costs to win.
Five decisions founder-led companies still make by hand
Each one is a recurring call with known inputs. Made by hand, it waits for someone to notice. Made by the operating layer, it becomes a scored, logged decision that a person approves where judgment is needed.
| Decision point | Current process | Latency | Operating layer |
|---|---|---|---|
| Inbound lead → priority | Web form to a shared inbox; whoever is free picks it up | hours–days | Scored and routed on arrival, with the account's history attached |
| Overdue invoice → follow-up | Noticed at month-end reconciliation | 30+ days | Flagged on day one; reminder drafted and queued for approval |
| Account → churn risk | Discovered at renewal or on cancellation | at renewal | Risk re-scored on every ticket, usage change and payment event |
| Spend request → approval | Email thread to the founder | days | Checked against budget and policy; auto-approved within set limits, escalated above them |
| Employee exit → access removal | Checklist from memory, tool by tool | days, often incomplete | Triggered by the HR event; access revoked across every connected tool and logged |
Exception-based reporting: changes, risks and pending decisions
Agents prepare the analysis. You and your team make the calls. For bigger decisions, such as a hire, a price change or a new market, you get a decision memo with the numbers laid out.
Cash: 7.5 months runway, down from 8.1. Two invoices ($18,400) 30+ days overdue.
Revenue: pipeline up 12%. Three deals stalled over two weeks.
Customers: onboarding tickets up 40%, mostly from the new pricing page.
People: one offboarding complete; access removed from 9 of 9 tools.
Compliance: payroll remittance due Friday; insurance renewal in 21 days.
Decisions this week: chase the two invoices; review the onboarding page.
Engagement tiers
Every package starts with a setup of two to four weeks. Pricing is set on a call, after your free X-ray.
Essentials
For founders who want the numbers in one place.
- Finance and revenue agents
- Live dashboard and alerts
- Monday operating brief
Operator
The full operating layer.
- All six agents
- Dashboard, brief and alerts
- Monthly operating review
- Decision memos on request
Partner
When you need judgment as well as data.
- Everything in Operator
- Hands-on fractional COO support
- Planning, process and key decisions
Native connectors to your systems of record
Anything else with an API or a data export can be added.
Task-level model routing. No single-vendor lock-in.
Each agent runs on the model that performs best for its task, balancing accuracy, speed, cost and where your data is processed. When a better model arrives, we switch the agent over without rebuilding your system.
Start with an operations X-ray: a scoped diagnostic.
Book your X-rayReference architecture: from hierarchical reporting to agent-orchestrated operations
How a conventional company moves information today, how an AI-native company does it, and what that looks like when it runs.
Conventional operating model: optimized for reporting, not decision speed
Most companies still run on a reporting pyramid. Information starts with the people closest to the customer and climbs through managers, directors and vice-presidents before it reaches the executives who can act on it. Each layer summarizes. By the time a signal arrives, it's weeks old and stripped of detail.
The problem isn't the people. It's an architecture designed to move reports, not decisions.
Signal path: the escalation chain
- OriginateSomeone on the front line logs an issue or tells a manager.
- FilterThe manager decides what to escalate. Routine items stop here.
- SummarizeA director rolls reports into a weekly summary. Detail is lost.
- AggregateVice-presidents compile monthly review slides.
- PresentExecutives decide on a summary of a summary, weeks later.
- CascadeThe decision travels back down. The situation may have changed.
Structural failure modes
Signal latency
Signals take weeks to reach the people who can act on them.
Fragmented systems of record
Finance, sales, support and HR each hold part of the picture. Reconciling them is manual and late.
Context loss at each layer
Every layer compresses. A detailed customer issue becomes a bullet, then a number.
Undocumented institutional knowledge
Critical know-how lives with individuals. When they leave, it leaves with them.
Cross-functional coordination overhead
Anything spanning departments needs meetings, committees and approval chains.
Point-in-time compliance evidence
Compliance evidence is gathered by hand before each audit, so gaps surface late.
AI-native operating model: unified data layer, specialist agents, governance by design
An AI-native company replaces the pyramid with a closed loop. Specialist agents sit inside each department, connected to the systems the team already uses. A coordinating agent in each department checks and reconciles what they find. A central command agent sees across every department and answers executives directly.
People stay in charge: they direct the work, review it and govern it.
Four architectural foundations
Unified data layer
One governed source of truth across finance, sales, operations and people. Agents query it in seconds, not at month-end.
Specialist agents
Agents with a defined scope, measurable tests and an audit trail in every department. Coordinators handle cross-team work.
Trust & governance layer
Identity-aware access, policy enforcement, redaction, testing and a full audit trail, applied before any information moves.
Role-scoped executive consoles
A view scoped to each role: live indicators, plain-language questions, and approvals within limits leaders set.
Structured decisions, not chat transcripts
Agents don't hand executives paragraphs to interpret. Each recurring call is defined as a decision: a known set of inputs, a structured output, and a confidence score. Above the threshold it proceeds; below it, a person reviews only the cases that are genuinely ambiguous. Because every decision is recorded with its score and any human correction, accuracy can be measured and improved over time.
# example · sample data decision invoice.follow_up inputs invoice: INV-2291 days_overdue: 34 account_tier: key payment_history: 2 late / 12 output action: draft_reminder tone: firm approver: CFO score 0.92 ≥ 0.85 → queued for one-click approval status logged · trust layer applied
Signal path: event-driven
- CaptureAn agent picks up an event from a connected system.
- CoordinateThe department coordinator checks it against related data.
- GovernThe trust layer applies access rules, redacts and logs.
- Cross-checkThe command agent compares it across departments.
- SurfaceThe executive sees it the same day, with sources attached.
- LearnThe outcome feeds back, so the next pass is better.
Domain coverage
Build the foundation first. Adding governance to agents that are already running costs far more than designing it in from the start.
Book your X-rayMulti-agent orchestration: live telemetry
The architecture in operation. The command agent sits at the centre, department coordinators form the ring, and specialist agents work at the edges. When something degrades, the department turns amber, the command agent investigates, and the issue is resolved while routine work continues. Select a department to inspect it.
Command agent
Sees across every department, cross-checks signals and answers executives directly.
Illustrative simulation. Every deployment is designed around the client's own departments and systems.
Natural-language queries with source attribution and role-based access
Each executive works with the command agent through an interface scoped to their role. They see only the departments they're authorized to access, every answer cites the systems it came from, and every exchange is logged.
Access scope
Every agent decision, with its score and the human call
| Time | Decision | Agent | Score | Outcome |
|---|---|---|---|---|
| 09:12 | Overdue invoice INV-2291 → draft reminder | Finance & treasury | 0.92 | Approved by CFO |
| 09:40 | Account Halden Co. → churn risk high | Customer operations | 0.78 | Reviewed; owner assigned |
| 10:05 | Spend request $4,200 → within policy | Finance & treasury | 0.96 | Auto-approved within limit |
| 10:31 | Inbound lead → priority A | Revenue intelligence | 0.64 | Corrected to B by head of BD |
All figures are sample data for a fictional company.
Vertical platforms: built, owned and operated by AIB2B
Where an industry still runs on phone calls, spreadsheets and email, we build the operating system it's missing. Each platform runs on the same foundation we build for our clients: agents that do the work, people who approve it, and security and support designed in from the first day.
Bid Desk Florida
Managers forward a job by email. Agents write the scope, invite vetted contractors and compare the bids. A person approves each step, and the manager receives a one-page board summary. Free to managers.
Read the case studyBluOrbit
Grant discovery, matching and drafting. A multi-agent system matches organizations to grants on structured eligibility criteria and prepares the application.
bluorbit.caCondoReach Florida
Outreach and bid support for contractors serving condo and HOA communities, with a monthly reach report for each territory.
condoreachflorida.comDeal Workbench
Acquisition diligence for professional-services firms. Gating documents, data-room intake, evidence-cited analysis, weighted target scoring, and a lender-ready business plan and financing package in one governed workflow.
Platform overviewEstatehood
Multi-tenant, white-label estate planning for law firms. Clients complete a guided AI intake by chat or voice; the firm's lawyer reviews every document before it's signed. Will, power of attorney for property and living will, Ontario first.
Platform overviewMulti-tenant estate planning: AI-guided intake, lawyer-reviewed documents
Roughly half of Canadian adults don't have a will, and most law firms can't serve them profitably one appointment at a time. Estatehood lets a firm offer wills, powers of attorney and living wills under its own brand: agents run the intake and draft the documents, and the firm's lawyer reviews and approves every one.
Status: pilot with a founding law-firm partner, launching November 2026. Built and operated by AIB2B. estatehood.ca
Client pipeline with a lawyer approval gate
Structured intake, not free-form chat
The conversation is the interface; the output is a typed intake record. Each answer maps to a field the template needs, with a completeness score. Ambiguous or high-risk answers, such as a blended family or a business interest, are routed to the lawyer rather than resolved by the model.
# example · fictional client decision intake.readiness inputs intake_record, province: ON, service: will + poa_property output completeness: 0.94 flags: [blended_family] route: lawyer_review score 0.94 → draft generated, flag attached status logged · awaiting lawyer approval
Agent-assisted acquisition diligence, from first conversation to financing package
Buying an owner-run firm means weeks of chasing documents, reconciling statements and rebuilding the same lender package by hand. Deal Workbench runs that as one pipeline: agents generate, parse, analyze and draft; the acquirer confirms every score and signs every document.
Status: in development. Built on the same foundation as our other platforms.
Seven-stage pipeline with gated data access
Weighted target scoring with knockouts and floors
Seven weighted dimensions, from financial quality and client concentration to owner dependence, transformation upside and exit attractiveness. Hard knockouts, such as debt-service coverage on as-is cash flow and earnings that survive a quality-of-earnings review, reject a target regardless of its weighted score.
# example · fictional target decision target.assessment inputs statements, returns, a/r aging, client list, add-backs, transcripts output weighted_score: 4.00 / 5.00 knockouts: 8 / 8 passed floors: transformation ≥ 3 ✓ verdict: strong_buy evidence cited per dimension status pending acquirer confirmation
Proven in production: every pattern runs on our own platforms first
Running a platform ourselves keeps us honest. Every agent pattern, security control and support process we offer clients has to work on our own systems first, under our own name.
- Separate environments and data for every platform and every client
- Changes tested in staging before anything reaches live
- Named people responsible for each platform's support
- Your data is never sold, and never used to train AI models
Bid Desk Florida: agent-orchestrated procurement for condominium associations
Property managers spend hours every week writing requests, chasing contractors and comparing bids that don't line up. Bid Desk Florida turns that into one forwarded email. It's built and operated by AIB2B on the same foundation we run for our clients.
Manual, unstructured procurement workflows
a week spent managing bids, by industry estimates.
Four and a Half
of vendors asked for a proposal actually send one.
Four and a Half
price spread between bids for the same job, because scopes don't match.
Four and a Half
Boards want three bids, compared like for like, before every meeting. Managers carry eight to ten associations or more. The work in between, writing, chasing, comparing and filing, is exactly the kind of operations work agents can take on, with people approving the result.
An eight-agent pipeline with two human approval gates
Nothing reaches a contractor or a board without a person looking at it first.
Decisions with confidence scores
Two of the calls Bid Desk makes on every request. Each returns a structured result and a score. Below the threshold, a coordinator reviews it before anything moves.
Bid-request triage
Reads the forwarded email, photos and attachments, and classifies the job before a scope is drafted.
in email, photos[], building, reserve_line? out trade: roofing urgency: high scope_ready: false → missing roof area score 0.88 ≥ 0.80 → proceed to scope
Contractor-fit scoring
Ranks vetted contractors for the approved scope by trade, county, insurance and track record.
in scope, county, trade, coi_status, record out shortlist: [A 0.93, B 0.87, C 0.81] excluded: D → insurance expired score 0.87 → invites queued for approval
Illustrative signatures. Field names simplified for display.
The same production foundation we deploy for clients
Bid Desk handles other organizations' information from the first live bid. So it runs on the standards we build for every client, not on a shortcut.
Tenant isolation & least privilege
Each property's data kept separate, least-privilege access, encryption, and an audit log of every action.
Staged release pipeline
Every change is tested in a separate staging environment and approved before it reaches managers.
Human approval gates
Agents do the legwork. Named coordinators review scopes and comparisons before anything goes out.
Monitoring, backup & data portability
Monitoring, daily backups, and bid history managers can export at any time.
From inbound email to board-ready bid packet
- The manager forwards the job
A photo, an engineer's note or a reserve study line is enough. No login.
- Bid Desk writes the scope
Quantities, access, hours and insurance requirements, checked by a coordinator.
- Vetted contractors bid
Two or three from the network, plus the manager's own vendors.
- The comparison is built
Prices on the same basis, gaps flagged, one-page board summary.
- The board decides
The award is recorded and handed to the property's accounting system.
Results from the first months of operation will be published here after launch.
Still running procurement on calls and spreadsheets?
Let's map what an operating layer would change for you.
Engineered for production, not demos
Most AI projects stall because they're bolted onto old work. We design agents into the work, prove one workflow first, and keep people on every decision that needs judgment.
Release engineering
Separate staging and live environments. Every change tested and approved before it goes live.
Human approval controls
Agents gather, draft and compare. A person reviews before anything important goes out.
Security architecture
Least-privilege access, encryption, separate environments for every client, and a full audit log.
Monitoring & incident response
Systems watched around the clock, with named people responsible for each one.
Data sovereignty
Never sold and never used to train AI models. It stays in your accounts wherever possible.
Continuity & portability
Documented systems, daily backups and data you can export at any time.
Invariants every deployment enforces
These hold on every client system and on our own platforms. They're designed in from day one, because adding governance to agents that are already running costs far more.
- No agent moves money without approval
Payments, refunds and commitments always pass a named approver.
- Every decision is logged
Inputs, output, score and any human correction, kept as an audit trail.
- The client owns the data
Your systems stay the record. Agents read and write through scoped access, never a copy we keep.
- Access is scoped by role
Each agent and each executive sees only the domains it is authorized for.
- Models are swappable
Agents call models through one interface, so a model can change without a rebuild.
Engagement lifecycle
- Operations X-ray
Free, 30 minutes, with a one-page map in three business days.
- 30-day pilot
Two systems connected, usually finance and revenue, plus your first Monday briefs.
- Full setup
Every core system connected and all agents live, in two to four weeks.
- Run and grow
Monthly reviews, agent tuning and new areas as your company grows.
Operations X-ray: a scoped diagnostic of your operating architecture
We map how your business runs today: where your numbers live, what's disconnected, and what you're not seeing. You get a one-page operations map within three business days. No obligation.
Deliverables
- Your systems and how they connect today
- Your five biggest blind spots, in order of risk
- Three quick wins you can act on right away
- What an operating layer would show you, with scope and cost
No passwords and no system access. The X-ray is a conversation, not an audit of your accounts.
One decision, run in parallel, measured, then scaled or stopped
After the X-ray, nothing is migrated and nothing is replaced. We prove one decision first, side by side with how your team makes it today.
- Select
Pick one recurring decision that costs your team time today, from the X-ray findings.
- Shadow run
The agent makes the same call alongside your team, with no access to act. Both answers are logged.
- Measure
You get the numbers: accuracy against your team, time to decision, and cost per 1,000 decisions.
- Scale or stop
If it clears the bar, we widen it to more decisions. If it doesn't, we stop and tell you why.
Start an architecture conversation
Questions about the operating layer, our platforms or a partnership. We reply within one business day.