
Digitate announced a bundled SaaS offering with BMC's Control-M platform on the AWS Marketplace.
The new offering brings Digitate’s AIOps capabilities to enterprise batch workloads for ensuring that organizations predict and prevent violations of business SLAs and on-time delivery of key business outcomes, autonomously. The solution is offered as part of the Multi-Product Solutions, a new capability of the AWS Marketplace that streamlines enterprise procurement by allowing customers to purchase complete and integrated solutions in a single transaction. Digitate and BMC are the launch partners to the AWS Marketplace for the Multi-Product Solutions.
The Control-M solution, powered by Digitate’s ignio™ AI Agent for AIOps, takes simplified workflow orchestration across hybrid and multi-cloud environments to the next level, making it easy to define, schedule, manage, and monitor complex application workflows. Control-M integrates, automates, and orchestrates application workflows across on-premises, private, and public clouds, ensuring visibility, reliability, and improved SLAs. With a unified view and a rich library of plug-ins, organizations can orchestrate all workflows, including file transfers, applications, data sources, and infrastructure.
Digitate’s AI Agents bring AIOps to the Control-M platform through advanced anomaly detection, auto-triaging, and proactive problem management. This agentic solution delivers business SLA prediction, helping organizations predict and prevent violations of business SLAs and ensure on-time delivery of key business outcomes. ignio’s AI agents perceive, reason, act, and learn to deliver measurable business value, transforming batch operations for the autonomous enterprise—including IT event management, incident resolution, business SLA prediction, and proactive problem management.
AWS Marketplace’s Multi-Product Solutions, launching at AWS re:Invent 2025, allows sellers to combine complementary products into unified solution listings or transact bundled solutions through private offers. This innovation streamlines procurement for enterprise leaders and CxOs, reducing complexity and accelerating time-to-value.
Key Benefits for Customers:
- One-click purchase of a complete automation solution through AWS Marketplace.
- Bundled offering combining Digitate’s AI-driven automation with BMC’s Control-M capabilities, delivering holistic IT operations management.
- Agentic AI solution to prevent business SLA failures impacting on-time delivery of key business deliverables through AIOps—detecting anomalies, auto-triaging, self-healing, and proactive problem management of batch workloads.
Abhijit Deshpande, Global Head of Ecosystems at Digitate says, "Digitate is committed to transforming enterprise IT operations to become autonomous. The solution created by partnering with BMC Software accelerates the vision of autonomous IT for batch operations. By bundling our agentic AI platform, ignio, with BMC’s Control-M, enterprises can deliver business outcomes on time.”
“Our collaboration with Digitate and AWS is a force multiplier,” said Brian Jones, Global VP Strategic Partnerships, BMC. “Together, we are delivering an integrated, AI-powered solution that simplifies procurement and accelerates enterprise automation. This offering brings unmatched intelligence, resilience, and operational efficiency to customers looking to modernize at scale.”
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.