Scaling Enterprise Support: Atomicwork's Journey to Seamless AI quality with Maxim

Scaling Enterprise Support: Atomicwork's Journey to Seamless AI quality with Maxim

About Atomicwork

Atomicwork is an agentic service management platform that helps businesses automate IT, HR, and workplace support, enabling employees to solve issues faster, work smarter, and stay productive. Built AI-native, Atomicwork combines intelligent agents, adaptive workflows, and enterprise-grade governance to deliver proactive support right in the flow of work. Leading enterprises trust Atomicwork to modernize internal support and transform the workplace experience.

Atomicwork’s AI-Powered Support Ecosystem

Going beyond traditional service management, Atomicwork unifies an intelligent AI support stack with a full-stack service management platform, proactively handling employee needs across every channel.

A few of the standout features of Atomicwork’s AI-powered platform include:

  1. Atomicwork’s Universal Agent, Atom, delivers proactive, multimodal support with Voice and Vision AI, enabling real-time assistance for employees across Slack and Teams, the browser, and email.
  2. Atomicwork’s AI Agents autonomously orchestrate enterprise workflows like diagnostics, knowledge management, incident triaging, and operations monitoring, accelerating resolution times across IT and business operations.
  3. AI-powered Enterprise Search unifies scattered knowledge sources, systems of record, employee data, and contextual insights, helping employees instantly find accurate answers across multiple systems and reducing time spent searching for information.

This AI-first approach enables enterprise-grade support automation, boosting efficiency, cutting costs, and helping teams focus on higher-impact work.

Challenges

The Atomicwork team is dedicated to enhancing their service management platform, but as they scaled, evaluating and monitoring an expanding suite of AI features became increasingly challenging. While engineering efforts remained key to delivering high-quality solutions, the growing complexity of systems  introduced new challenges for cross-team collaboration. The team identified key areas to optimize, including:

  • Ensuring consistent AI quality across diverse workflows, models, and prompts as the system evolved
  • Enhancing visibility across workflows, including LLMs and interconnected systems, making it easier to detect and diagnose issues.
  • Accelerating debugging and issue resolution during production.

To meet these demands, the team recognized the need for a more scalable, efficient way to test, monitor, and iterate, reinforcing their commitment to delivering reliable, high-quality AI support.

How Atomicwork Delivers Reliable AI—Faster with Maxim

With expanding AI capabilities, Atomicwork needed a solution to evaluate, monitor, and continuously improve their AI workflows—without slowing down development.

That’s where Maxim AI came in. As an early adopter, Atomicwork’s team has deeply integrated Maxim’s end-to-end AI quality platform into their development cycle, ensuring effective AI interactions, system reliability, and observability at every stage.Atomicwork’s team systematically builds, tests, deploys, and improves AI models using Maxim AI. Here’s how:

  • Pre-Deployment AI Evaluation: Every model or AI-powered feature meets strict benchmarks through Maxim’s automated evaluation workflows before going live.
    • Prompt Playground – Teams test and refine prompts and holistic workflows before production.
    • Structured Comparison Reports – Models are benchmarked against curated datasets and key evaluation metrics to assess accuracy, coherence, and reliability.
    • Validation Checks – Automated evaluations confirm response correctness, consistency, and contextual accuracy before final deployment.
  • Observability & Real-Time Monitoring: Atomicwork ensures full visibility into AI behavior with Maxim AI’s monitoring and logging capabilities once in production.
    • Granular AI Logs – Every retrieval, generation, tool call, API request, and trace is captured for analysis. This extends not just to text interactions but audio and video interactions as well, with Maxim seamlessly tracing these multimodal engagements to ensure end-to-end visibility across all communication modes.
    • Universal Search & Debugging – Teams can filter logs by models, metadata, prompts, workflows, and components for faster troubleshooting.
    • Jump from Traces to Prompt Playground – Engineers quickly debug AI behavior by tracing issues back to specific prompts and workflows, refining them in real-time for better outputs.
  • Using Production Data to Improve AI: Atomicwork’s team actively leverages production data to enhance model training, prompt workflows, and evaluation datasets. By curating high-quality datasets directly from AI interactions, Atomicwork continuously improves reliability and performance in real-world conditions.

With Maxim AI embedded in their pipeline, Atomicwork’s team ships AI updates faster, with confidence in quality and reliability.

Impact 

Atomicwork’s cross-functional teams across AI/ML, Engineering, Product Management, QA, and Customer Success have been using Maxim to raise the bar on AI quality and reliability constantly. 

By integrating Maxim AI, Atomicwork has streamlined AI evaluation, debugging, and continuous improvement—without slowing down releases. 

"Maxim has been a game-changer for our AI quality journey. From the start, multiple teams have relied on Maxim for comprehensive end-to-end testing and monitoring of all our AI features, enabling us to scale efficiently and consistently deliver high-quality results.”

- Suresh Ponnusamy, Head of Platform Engineering, Atomicwork

Real-time observability with Maxim has helped the team catch and resolve AI issues much faster. With Maxim’s AI logs and debugging tools, the team can trace failures instantly, pinpoint issues in responses, and optimize performance on the fly. Instead of sifting through scattered logs, they can filter search by model, prompt, or metadata and get to the root cause in seconds.

The CSM team reduced troubleshooting time by nearly 30% in the last 3 months with instant visibility into customer issues, powered by Maxim’s granular logs and automated trace analysis. 

"Maxim’s tracing and metadata filtering capabilities let us pinpoint issues instantly instead of spending hours searching through scattered logs. We can now confidently scale our AI features, knowing we have complete observability from prompts to final outputs."

- Shanthi Vardhan, Head of AI Platform, Atomicwork

Atomicwork is also actively improving AI quality using real-world data. By leveraging AI logs as structured feedback, they’re able to refine evaluation datasets based on production interactions, leading to more accurate and reliable AI over time.

“The ability to curate high-quality datasets from execution traces and integrate AI observability directly into both development and production environments has significantly streamlined our operations.”

- Shanthi Vardhan, Head of AI Platform, Atomicwork

With Maxim AI, Atomicwork has:
✅ Accelerated AI updates without sacrificing quality
✅ Identified and resolved AI issues faster with real-time logs & debugging
✅ Used production data to improve AI accuracy via structured dataset refinement

By integrating AI quality checks at every stage, Atomicwork has made continuous improvement a foundational part of how they build and scale intelligent workplace solutions.

AI Innovation with Enterprise-Grade Security

All of this happens inside Atomicwork’s secure VPC, which keeps every test, evaluation, and model iteration entirely within their controlled environment. By deploying Maxim AI on-premises, Atomicwork ensures that all testing and optimization processes remain entirely within their secure network, with no data leaving their environment. The seamless combination of Maxim's advanced evaluation capabilities and robust security measures empowers Atomicwork to innovate confidently while upholding customer trust.

"In the enterprise space, privacy and security are critical. Maxim's on-premises deployment within our VPC gives us all the benefits of advanced AI evaluation while keeping our data entirely within our secure environment — a critical requirement for our largest customers."

- Suresh Ponnusamy, Head of Platform Engineering, Atomicwork

Conclusion

Atomicwork is expanding its use of Maxim AI to enhance AI-driven workflows. A key focus is implementing Maxim AI’s workflow simulation feature. This will enable the team to simulate user interactions pre-release, ensuring more effective task-based success evaluation, regression testing and robust validation of agent-driven workflows.To streamline operations, Atomicwork plans to automate AI evaluations within CI/CD pipelines using Maxim AI’s GitHub Actions integration. This will allow models to meet quality benchmarks with every development cycle, removing manual bottlenecks and speeding up deployment.

Additionally, proactive Slack Alerts and Summary Reports will notify teams of performance shifts, anomalies, or failures, driving faster response times and more efficient debugging. Atomicwork continues to leverage tracing tools for debugging, enabling efficient identification of production-time issues and evaluation of datasets. At the same time, improved workflow monitoring enhances post-release visibility, ensuring smooth operations even beyond major updates. Privacy and security remain top priorities, with NVPC deployment keeping customer data secure within their own VPC and network.

As they continue to build smarter workflows, Maxim AI plays a key role in scaling Atomicwork’s AI-driven solutions while upholding high standards of quality and security.

At Maxim AI, we share this vision and are dedicated to empowering teams building AI-first products. If you’re looking to streamline AI deployment and iteration, let’s connect.

Learn more about Maxim here: getmaxim.ai
Learn more about Atomicwork here: www.atomicwork.com