eG Innovations has successfully met the SOC 2 Type 2 compliance requirements.
An independent, CPA audit confirmed that the company's internal processes and procedures as it relates to software development, delivery and SaaS services are safe and effective and that they meet or exceed the internal controls required for safeguarding customer data according to the American Institute of Certified Public Accounts (AICPA) Trust Service Criteria.
eG Innovations uses Amazon Web Services (AWS) to deliver its SaaS offerings and this report shows that suitable safeguards, best practices, and controls are in place to achieve service commitments and requirements based on the applicable trust services criteria.
Raja Kannan, Head - Technology Services at eG Innovations said "The SOC 2 Type 2 report proves that eG Innovations meets the industry standards for designing controls and processes and that we take the safeguarding of customer data extremely seriously. The report came after months of auditing to ensure that our processes are robust enough to protect customer data over an extended time period."
This independent audit was carried out by Certified Public Accountants from Q1 to Q3 of 2022. They assessed all key HR, hiring, finance, DevOps, delivery and operations controls and processes and certified that all these controls operated effectively throughout the audit period. Furthermore, it is their opinion that these controls provide assurance that the company's service commitments would be achieved based on the applicable trust services criteria.
Karthik Ganesan, Head of IT at eG Innovations added "Security of our customers data and our software solution has always been our priority and I'm delighted that the SOC 2 Type 2 audit confirms this. This is testimony to how seriously we take our commitment to the design, control and processes towards data protection."
The SOC 2 Type 2 audit report for eG Innovations is available on request and outlines the controls and processes the company has designed to safeguard customer data, and the assurances that its service commitments were achieved.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...
The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...
Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...
If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...