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Enterprise AI in Production

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Akash Sathish

Akash Sathish

When the agent workflow survives production but the MCP server splits an RCE

Every enterprise AI workflow that matters in 2026 routes through MCP servers starting from the tools that give your AI agents access to files, databases, APIs, till shell commands. But the security posture of these servers is systematically poor: 43% have command injection vulnerabilities, 36% have SSRF exposure, and the real CVEs (CVE-2025-6514, CVSS 9.6) are execSync(args.cmd). These are bugs t… more
  • 2 comments
  • Submitted
  • 31 May 2026
Submission type: Anchor talk (30 mins)

Vivek Kalyanarangan

₹11 Lakh/Month: How We Took the GPU Out of Face Match

Face matching is one of the highest-volume workloads in identity verification. At IDfy, a single GPU pod handling 1 RPS cost us ₹3,500/day. After moving the model to BF16 inference on Intel CPUs via OpenVINO, the same 1 RPS pod cost ₹350/day. Same TAT, same throughput, same accuracy envelope. At our traffic shape (50 RPS sustained for the peak hour, 10 RPS for the remaining 23), that translates t… more
  • 0 comments
  • Submitted
  • 26 May 2026
Submission type: Anchor talk (30 mins)
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