We build and run AI agents that carry real operational work — answering customers, moving data between systems, searching what your company already knows, watching your cloud. Every action they take waits for a person to approve it.
Storage account left open to public network
tfmsp-backups-prod allows access from all networks. Proposed change:
restrict to the office and VPN ranges, keep the backup service exception.
An agent that can act on its own is a liability in a business with customers, money and compliance obligations. Ours propose; your team decides. Every proposal keeps its reasoning, and every decision is written down.
It states what it wants to do, why, and what it expects to change.
One of your people approves, edits or declines. Nothing moves without this step.
Only the approved action runs, and the record of who approved it stays.
Start with one. Most clients begin with whichever queue is loudest, then add the next once it is running clean.
Answers the phone and the chat window at 2am.
Handles inbound questions over chat and voice, qualifies leads against the criteria you set, and books appointments straight into your calendar. Anything it cannot answer goes to a person with the whole conversation attached.
Moves data between the systems that do not talk to each other.
Connects your CRM, email, scheduling and invoicing so a job booked in one place shows up everywhere it should. The handoffs your team does by copy and paste happen on their own.
Finds the answer buried in a folder somebody left behind.
An internal assistant that searches your documents, contracts and past tickets, drafts the email you were about to write, and cuts long reports down to the part you needed.
Watches your Azure environment the way an engineer would.
Monitors your cloud and security posture, flags what looks wrong, and proposes the fix with its reasoning attached. It extends the monitoring our Cybersecurity and IT Infrastructure teams already run for you.
Works alongside Cybersecurity and IT Infrastructure Services.
We sit with your team and map the work that repeats — the inboxes, the handoffs, the reports nobody enjoys building.
We score each task on volume, risk and how easily its output can be checked, then agree which ones are worth handing to an agent.
We build the agent against your real systems and wire the approval step in from the first day, not as an afterthought.
We run it, monitor it and report what it did each month, adjusting as your process changes.
Tech-Force built these agents for its own operating companies — a transportation business and a home care business — before offering them to clients. The customer response agent takes their after-hours calls, the operations agent moves bookings into invoicing, and the cloud agent watches the same Azure tenancy our engineers do.
So we can show you a system that has run in production against real customers, not a demo built for the meeting.
Book a free AI Readiness AuditBuilt on the systems you already pay for
If a system has an API, an agent can usually work with it. If it does not, we tell you that in the audit rather than after the invoice.
No. Agents propose; a person decides. That is the whole design, not a setting we can be talked out of.
Read-only work — searching your documents, summarising a report, answering a question — happens without a gate, because nothing changes. Anything that writes, sends, pays or reconfigures waits for a human.
Only the systems you connect and only the scopes you grant, using your own accounts and permissions. An agent cannot reach something a person in that role could not reach.
We document what each agent can see before it goes live, and you can revoke access at any time.
A wrong proposal gets declined, which costs you a few seconds. That is the point of the approval step — mistakes surface as suggestions rather than as actions you have to undo.
Every proposal and every decision is logged, so a pattern of bad suggestions is visible and fixable.
Weeks rather than months for a first agent on a well-defined workflow. The audit tells you which one that is.
We would rather have one agent working properly than four half-configured.
It depends on the systems involved and how much work the agent carries, so the readiness audit exists to answer that before you commit to anything.
The audit itself is free, and it ends with an honest view — including where automation is not worth it for you yet.
No. Agents work against what you already run — your CRM, your mailbox, your scheduling, your Azure tenancy. If a system has an API, an agent can usually work with it.
The AI Readiness Audit is a working session, not a pitch. We look at your systems, your volumes and what your team spends its week on, then tell you honestly what is worth automating.
