Do You Know What Your AI Agent Is Doing Right Now?
You don't want to become the next AI horror story filled with duplicate records, wrong answers, triggering unintended workflows, and cost spikes.
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Our AI Agent Operations ensures you're a headline-worthy success ... and with ability to scale across every agentic application in your organization.
Nina’s team finally launched their first AI agent into production to automate internal workflows.
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Answer employee questions, retrieve data from multiple systems, and perform simple operational tasks that previously required manual effort. At first, the results looked promising ... but within weeks, new issues started appearing.
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The agent was calling multiple systems in the background, slowing things down. Sometimes, it triggered workflows that weren't supposed to run - in instance, it build dozens of duplicate records that took hours to clean up! And to top it all off, a spike in cloud usage tripled the bill.
Leadership still loved the idea of AI agents, but confidence in this one? Gone.
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And now Nina, their Director of Digital Transformation, realized the problem wasn’t the model or the idea of agentic AI, but the lack of operational controls around how the agent operated with data retrieval, triggered actions, and behavior inside real business systems.
Building an AI agent is the starting line, not the finish; it's ongoing operation needs more.
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Because without the proper oversight, your AI agent operations falls apart.
Solve These Challenges
AI Agents Create More Work Vs. Savings
Teams waste hours fixing AI-generated errors, including rekeying orders or copying data across systems.
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When Something Breaks, It's Impossible To Tell Why
Attribution, logs, and/or review paths for AI actions are buried or incomplete.
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One Upstream Change Breaks It All
One failure derails an entire automation, driving lack of user confidence.
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AI Usage Costs Aren't Predictable
Automation-driven consumption spikes lead to budget surprises
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Realize Gains Such As:
Measurable KPIs
10% lower costs with greater predictability
25% increase in tasks completed without needing re-work
Mean response times below 20 seconds
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Operational Wins
Costs stay predictable as your teams benefit from a full audit trail for every AI-initiated action backed by incident response playbooks and policy-aligned guardrails
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Executive Wins
AI that Operations, Legal, and Compliance all support because every action is logged and every incident has a plan.
Trusted By:
You don't need more fires to put out. And that's why we're here.
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We actively monitor everything, compile useful information for improvement, report on what's working vs. isn't, and ship improvements.
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You get a running issue log, health summary, clear priorities, and shipping / validated agent changes on a rolling basis.
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The end result? Actual results that matter.
How You Stay On Target
The last thing you want is for excited fanfare at your agent's launch to immediately turn into frustration and a lack of adoption.
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Active monitoring, monthly governance reviews, and cross-checking the agent's knowledge base vs. results are handled on an ongoing monthly basis.
Your agent stays accurate from the outset. People use it more.
We Work
Across Systems, Including:
“The scoping process was spot-on. We had a great experience with the DoubleTrack team."
ClearDATA
How We Help: AI Agent Operations
We build reliable, governed AI automation layers that span sales, finance, purchasing, support, marketing, and save IT significant hassle. Work includes:
Workflow Identification & Decomposition
Agent Governance
Reliability Engineering
Telemetry Setup
Secure Integrations
Shadow Mode &
Production Rollout
Build AI Agents that work the first time - and every time.
Most AI agent deployments lack the business-critical layer that keeps AI from going rogue: audit trails, cost guaradrails, and fallback logic.
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We bring the data-first approach to AI Agentic Operations so it runs smoothly & builds user and executive confidence.
SUCCESS STORIES
Customers like you are on the right track
What's the difference between building an AI agent and operating one?
Building an agent is a one-time implementation involving connecting a model to your data, configuring prompts, and deploying.
Operating an agent is the ongoing work that determines whether the deployment actually succeeds: monitoring outputs, maintaining audit trails, tuning responses as business conditions change, and managing costs connected to use.
Most organizations invest heavily in the build and under-invest in the operation, which invites drift and hallucinations.
How do you monitor AI agents in production?
Effective AI agent monitoring tracks not just what the agent gives in its answers and its processes, but how users are interacting with it (i.e. how questions are phrased or how the agent interprets follow-ups).
DoubleTrack's AI agent operations practice captures all of this, with defined review rhythms and feedback loops built in from day one.
What is AI agent operations?
AI agent operations is the ongoing practice of monitoring, governing, and continuously tuning deployed AI agents to ensure they perform reliably in production.
Unlike traditional software, AI agents adapt in real-time to new data, conversations, and guidance ... and this means they can drift over time as data changes and usage patterns evolve.
Effective AI Agentic Operations catches that drift before it reaches customers or creates operational errors.
Frequently Asked Questions
The trend continues growing: AI pilots never reaching production because they're built on the wrong foundations. Andy Boettcher explains more (and what to do to avoid becoming the statistic)
Let's Talk
On Your Schedule
Schedule a time that works best for you, and we look forward to learning how we can help - and adding value right away.
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Want to call us? (844) 4DATAVALUE