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Tirth Gajjar

CTO at BigCircle and CTO at Indexa Exchange Group

Agentic AIEnterprise RAGLLMOpsCapital Markets InfrastructureAWS ArchitectureMulti-agent Collaboration

About

I'm Tirth Gajjar, currently serving as CTO at BigCircle and Indexa Exchange Group. My career has been defined by a transition from hands-on engineering to architecting complex, production-grade systems. At BigCircle, I lead an AI-native studio focused on agentic workflows, while at Indexa, I oversee institutional-grade infrastructure for capital markets. I am deeply passionate about moving AI beyond 'demo theater' and into reliable, enterprise-scale deployments. I believe that true AI value lies in system design and deterministic control rather than just model intelligence. I'm here to offer fractional CTO expertise and embedded engineering squads to those looking to bridge the gap between operational challenges and realistic AI capabilities. Whether you are a venture-backed founder or part of a CIO team, I'm interested in discussing how we can move from simple efficiency to genuine growth and reinvention.

Networking

What I can offer

  • Fractional CTO partnerships
  • Embedded engineering squads
  • Expertise in MCP-based system design
  • RAG infrastructure implementation

Looking for

  • CIO/CTO teams
  • Venture-backed founders
  • Government bodies looking for practical AI solutions

Best fit for

CIO/CTO teamsVenture-backed foundersGovernment bodies

Current Interests

Production-Grade AIAgentic WorkflowsSystem Safety and GuardrailsGovTech and Public SystemsMCP-based system design

Background

Career

Transitioned from a software developer and consultant into high-level technical leadership, founding an AI studio and serving as CTO for capital markets and innovation-focused firms.

Education

Bachelor’s Degree, Information and Communication Technology, Dhirubhai Ambani University (2013–2017)

Achievements

  • Built BigCircle into a globally competitive AI studio
  • Architected multi-tenant infrastructure for Indexa to manage benchmarked assets
  • Developed autonomous voice agents for the insurance sector
  • Created sustainability data platforms for tracking environmentally responsible companies

Opinions

  • AI failures in production are usually due to poor system design rather than model limitations
  • Engineering control determines reliability more than optimizing intelligence
  • AI value should move from simple efficiency to growth and reinvention
  • Skeptical of incremental model releases; values execution-driven engineering over buzzwords