Calsoft to Host AI Ops Meetup in Pune on Jan 17
Wednesday, January 14, 2026
Calsoft is organising a technical meetup on Operations for AI Applications on January 17, 2026 (Pune, India). The event will bring together industry practitioners to share practical insights on building and managing CI/CD pipelines, observability frameworks and FinOps strategies tailored for AI workloads. Hosted in collaboration with AI Circle (AICircle.Dev), a community focused on AI and MLOps, the meetup is designed to spotlight real-world operational challenges enterprises encounter while deploying and scaling AI applications in production; and to encourage informed discussions around proven approaches and best practices.
𝐐𝐮𝐢𝐜𝐤 𝐕𝐢𝐞𝐰
- Event focus - CI/CD, observability and FinOps practices tailored for AI application operations
- Target audience - AI/ML engineers, DevOps engineers, data scientists and enterprise teams managing AI infrastructure and deployment costs
- Community collaboration - Part of AI Circle's ongoing initiative to facilitate knowledge sharing on AI operational best practices
The meetup will feature three technical sessions covering the operational lifecycle of AI applications.
Hemant Kumar will lead the opening session on CI/CD for AI, followed by Mukta Aphale’s presentation on observability for AI systems. Rajshekhar Chavakula, Senior Technical Architect, Calsoft, will conclude the technical programme with a session on FinOps in AI. The event will also include a dedicated networking session, giving attendees an opportunity to exchange insights and discuss implementation strategies.
The sessions are designed to address specific operational challenges in AI deployment that differ from traditional software operations. CI/CD practices for AI must account for model versioning, data pipeline dependencies and retraining workflows. Observability requirements extend beyond standard application monitoring to include model performance tracking, data drift detection and inference latency analysis. FinOps considerations become critical as AI workloads consume significant compute resources, particularly with GPU usage and large-scale model serving.
As organisations accelerate AI adoption, the gap between model development and production deployment has emerged as a key bottleneck. Teams working with machine learning pipelines and large language models face unique challenges in maintaining operational efficiency while managing infrastructure costs and ensuring model reliability at scale.
"As enterprises scale their AI initiatives, operational efficiency becomes as critical as model accuracy," said Shrish Ashtaputre, Senior Technical Director, Calsoft. "This meetup brings together practitioners to share real-world approaches to CI/CD, observability and cost management; the three pillars that determine whether AI applications succeed in production."
The event is open to AI/ML engineers bridging research and production implementation, DevOps engineers transitioning to MLOps and LLMOps; and data scientists collaborating with operational teams to move from experimentation to scalable deployments. AI Circle serves as the community platform for professionals exploring and mastering AI operational practices.
