AI agents that
do real work,
built to be trusted.
DeployCo custom-builds, deploys, and operates AI agents for your business, each one built for a specific job, from back-office work like invoices and reconciliation to customer-facing workflows. Agents run on DeployCo managed infrastructure or are deployed into your environment, to your specification. Consequential actions wait for your approval, and agents earn expanded autonomy only through proven performance.
Agents that do the work, not just describe it.
Every action waits for your one-tap approval.
Built for specific jobs.
Built for your business.
Each agent does one job, done well. These are common categories of work agents are built to operate.
Ticket resolution, end to end
Classifies incoming tickets, pulls the order or account history, and resolves the routine ones: issuing the refund, requesting the reshipment, closing the loop. The cases that need human judgment are escalated with full context. Your team sees fewer tickets, and the ones they see are the ones that matter.
Inbound lead response
Replies to new lead submissions within minutes, qualifies them against your criteria, sends a personalized first response, and books the meeting on your calendar, logging it to your CRM. The hours your team spent chasing follow-ups go back to closing.
Inventory and reordering
Scans stock levels, sell-through, and supplier lead times on a schedule, flags what is about to run out, and prepares the purchase orders before you hit zero. You approve the reorders; the agent handles the watching and the math.
Account health and churn signals
Reads usage, billing, and support sentiment across your accounts, surfaces the ones trending toward churn, and prepares the retention follow-up with the reason attached. The risk is caught while there is still time to act on it.
Invoice matching and AP
Matches incoming invoices against the purchase order and goods receipt line by line, schedules payment on what reconciles cleanly, and routes the discrepancies to your team. Exact and auditable, no guessing on the numbers.
Campaigns that run and optimize
Runs campaign variants against your audience, watches performance on a schedule, and proposes shifting spend toward what works. Every send and budget change is approved by you before it goes live.
Built for one job, not configured from a template
Each agent is designed in a working session with you. The goals, the tools it can use, the rules it operates under, and the boundaries of what it cannot touch, all defined at the configuration level and enforced in the runtime, not written in a policy document.
Consequential actions wait for your approval
By default, an agent proposes consequential actions and they wait in your approval queue. You approve, edit and approve, or reject. An agent earns more autonomy only through verified results, within limits you set, and a kill switch returns it to fully supervised at once. Every decision is recorded.
Operated and governed by us, not by your team
We design the agent, deploy it on managed infrastructure or into your environment, monitor it, and apply the governance layer. You review work in your queue. Building or running an AI team is not a prerequisite.
From discovery to a working agent in production.
Discovery call
45 minutes
We learn what the agent would do, where it would touch your business, and what would have to be true for you to trust it. We tell you whether this is a fit before discussing scope or cost. No pitch deck.
Design and build
1 – 3 weeks
Goals defined. Tools chosen. Rules and policies encoded at the configuration level, not in a runbook. Integrations wired into your existing systems. Approval flow configured to your team's structure.
Review outputs in production
Ongoing
The agent runs on managed infrastructure or in your own environment. Outputs land in your approval queue with full context: what triggered it, what the agent reasoned, what it produced. You approve, edit, or reject. Every decision is logged.
Monitor, govern, improve
Always
Drift, edge cases, governance gaps, and operational anomalies are detected and addressed by our team. You receive weekly summaries of what the agent did and where it needed your judgment most. The system gets sharper over time.
The operational guarantees
behind every engagement.
Consequential actions are approval-gated by default. An agent proposes the action and it waits in your queue until a person approves it. An agent earns more autonomy only through verified results, within limits you set, and a kill switch returns any agent to fully supervised operation at once.
Every action is recorded: agent runs, governance decisions, administrative changes in your workspace, and your team's approval decisions. Your compliance team can review the history and export it as CSV or JSON.
We do not sell access to your data, train models on your content, or share your inputs with anyone. The agents call commercial language models with prompts assembled from your configuration, and the outputs come back to you. That is the only data flow.