Teceze Agentic AI & Automated Workflows deploys goal-driven agents that work inside the systems you already run ITSM, identity, HR, finance, cloud. They complete multi-step processes end to end, escalate to a human when policy says they must, and log every action they take. Not a chatbot bolted onto your stack. A digital workforce operating within it.
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Scripted automation breaks the moment a process changes. Agentic AI reasons about the goal, chooses the steps, and adapts when the path shifts — inside boundaries you set and can prove to an auditor.
Each agent is given a goal, a set of tools and a policy boundary — then plans and executes the steps itself. Provision the access, reconcile the invoice, close the ticket. The output is a completed process, not a recommendation.
Real processes span five systems, not one. Agents work across ServiceNow, Microsoft 365, Entra ID, SAP, Workday and your bespoke connectors and — where no API exists — UI automation.
You decide what an agent may do alone, what needs approval, and what it must never touch. High-risk actions — payments, privileged access, data deletion — stop at a named approver with full context attached.
Every prompt, decision, tool call and system change is logged and replayable. Agents run under least-privilege service identities, and data—residency and retention rules are enforced at the platform layer, not by convention.
We extend what you’ve already bought — Copilot, Power Automate, ServiceNow, Entra ID, SAP, Workday and your bespoke connectors and — where no API exists — UI automation. Model choice stays yours, and stays portable as the market moves.
Agents are monitored like production services: success rate, escalation rate, cost per run, drift. Exceptions are reviewed weekly and become the next automation — so coverage widens each quarter instead of stalling after go-live.
These are the ranges our enterprise clients typically see on the first three to five processes they hand to agents. We baseline each process during discovery, then agree the target in the statement of work.
Handled by agents end to end, with humans retained only at approval and exception points.
Joiner-mover-leaver, access requests and invoice matching measured from request to completion.
Achieved by removing rework and handoffs, not by removing controls or oversight.
From discovery to a first governed agent running live on a real process in your environment.
We start with a two-week discovery : map candidate processes, score each on volume, rule stability and risk, and return a ranked backlog with an ROI estimate per process — before you commit to a build.
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RPA follows a fixed script. Change a screen, a form field or an approval rule and the bot breaks which is why most RPA estates spend more on maintenance than they saved. An agent is given the goal rather than the steps, and works out the path using the tools you’ve allowed it.
The ones with high volume, stable rules, a clear success definition and a contained blast radius. Typical first wins are joiner-mover-leaver, access and licence requests, ticket triage and enrichment, invoice and PO matching, vendor onboarding, and report assembly.
Yes, an agent that can’t act isn’t useful. Access is granted through dedicated service identities with least-privilege, scoped to named actions in named systems, and reviewed on the same cycle as any privileged account.
Agents are built with confidence thresholds. Below the threshold, the agent stops and hands the case to a human with everything it has gathered so the fallback is a faster human decision, not a failed process.
We’re model-agnostic and deploy within your tenancy or cloud account Azure OpenAI, AWS Bedrock, Google Vertex or an open-weight model hosted privately, depending on your data-residency and cost position.
Get In Touch
Schedule a 45-minute session with our automation architects. You’ll leave with a clear view of which of your processes are ready for agents, which aren’t, and what each one is worth.