Selector’s cover photo
Selector

Selector

Software Development

Santa Clara, CA 12,556 followers

Industry leading AIOps platform for operational intelligence.

About us

Selector AI is the industry leading AIOps platform designed to provide instant, real-time actionable insights for managing multi-domain network and application infrastructures. By bringing together multiple sources of data into one easy to use platform, IT teams can troubleshoot network issues faster, avoid downtime, reduce MTTR and improve efficiency.

Website
https://www.selector.ai
Industry
Software Development
Company size
51-200 employees
Headquarters
Santa Clara, CA
Type
Privately Held
Founded
2019
Specialties
AIOps, Analytics, Observability, Automation, Cloud, Network, APM, Monitoring, Data Center, Machine Learning, and event correlation

Products

Locations

Employees at Selector

Updates

  • Synthetic monitoring shouldn’t be one-size-fits-all. Traditional synthetics are often rigid, limited, and fail to reflect the complexity of today’s hybrid environments. That’s why we built Custom Synthetics—a powerful, programmable framework that lets you define what, how, and when to test, tailored exactly to your infrastructure. Whether you’re monitoring from user edge to backend, or simulating specific scenarios across distributed systems, Selector gives you flexibility without friction—no vendor lock-in, no bloated tooling, just precision and performance. Explore how modern teams are using Selector’s Custom Synthetics to level up their monitoring stack: https://lnkd.in/eiUaUnAt

  • LLMs alone won’t cut it for real-world network automation. At Selector, we combine domain-specific RAG, real-time telemetry, and explainable AI agents to drive true chat-to-action operations. Ask questions, get grounded answers, and trigger safe, automated actions — all within one AI-powered workflow. Explore how we’re building the next-gen network automation stack: https://lnkd.in/euWBvMgJ

  • Selector reposted this

    View profile for John Capobianco

    Head of DevRel@Selector | Artificial Intelligence Enthusiast and Pioneer | Network Automation | AIOps | Distinguished Speaker | Award winning author | Teacher

    Join me for a LIVE DEV session for a new Selector tool that will provide digram to configuration conversation using multi-stage AI and multi-modal models! If you are a network engineer or into AI or want to help with prompts and diagram ideas - I will be developing live and covering the code on YouTube! See you soon! Everyone welcome! Open safe space!

  • Join us for a webinar as we welcome Sebastian Maniak to the Selector team—plus, get a live walkthrough of a virtual topology he’s built and fully integrated with Selector. 👨💻 Discover Sebastian’s vision for AI-driven network operations 🔍 Explore a live demo of a fully integrated virtual topology ⚡ See how Selector’s Root Cause Analysis and Copilot accelerate diagnostics and resolution It's all happening July 30th at 12pm ET! Don’t miss this chance to see AIOps in action—register now: https://lnkd.in/e54pgJNW

  • In this powerful conversation from #CiscoLive, Selector’s John Capobianco joins Peter Sprygada of Itential to break down what real AI adoption looks like across infrastructure, security, and automation. Two years ago, AI in networking was a curiosity. Today, it’s the engine driving operational excellence — and Selector is helping make that possible. 🎯 Highlights: • AI is delivering real value — not just hype • MCP is the next must-know protocol • Closed-loop automation is here (and secure) • Network language models are game-changers • AI empowers engineers — not replaces them Selector is proud to partner with Itential to push this evolution forward. 🎥 Watch the full conversation: https://lnkd.in/dYD3Ztvq

  • In the last 18 months, we’ve deeply integrated LLMs into Selector’s platform—and we’ve learned a lot. From building Copilot, our natural language interface for network insight, to optimizing context pipelines and prompt engineering, we’ve hit both breakthroughs and bottlenecks. Check out our blog to read more about our biggest lessons: https://lnkd.in/dCzMrfzk

  • Why is Selector so resilient, scalable, and built to handle anything from outages to natural disasters? Because it’s built on three powerful pillars: ✅ Kubernetes ✅ Infrastructure as Code ✅ Microservices Architecture This trio doesn’t just keep the platform running - it lets us say yes to customer demands while maintaining deep observability and operational confidence. 💡 Want to see how this architecture powers modern network operations? Watch the webinar on-demand with John Capobianco & Varija Sriram here: https://lnkd.in/ed23ecqB

  • View organization page for Selector

    12,556 followers

    Love seeing how teams are streamlining operations by bringing real-time network insights directly into Slack. When AI and ML meet collaboration, the result is speed, clarity, and control - right where work happens. 👏

    View profile for Sebastian Maniak

    Focus on Machine Learning and Artificial Intelligence | Security | Observability | Automation | Technical Marketing

    Having the power to quickly view my topology and utilization of specific devices from #slack is powerful. #AI #ML Selector #slack

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  • No more deciphering query languages. No more waiting on someone technical. Just type your question—in Slack, Teams, Zoom, or any preferred ChatOps platform —and get plain-language answers in seconds. 💡 Observability meets accessibility. 🚀 Now everyone on your team can be data-driven. Ready to ask your infrastructure anything? Visit ➡️ https://lnkd.in/eySwSJDt

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  • Selector Packet Copilot just leveled up — faster, more stable, and now powered by Gemini Flash 2.5. From metadata filtering to AI-driven IP insights, it’s built to handle even the toughest PCAPs. Coolest part? It’s free, open source, and seeing creative use from pros and newcomers alike. Curious what your packet might say? packetcopilot.selector.ai

    View profile for John Capobianco

    Head of DevRel@Selector | Artificial Intelligence Enthusiast and Pioneer | Network Automation | AIOps | Distinguished Speaker | Award winning author | Teacher

    A quick update on Selector Packet Copilot ! Some enhancements and slight modifications such as local embeddings have enabled us to overcome some previous limitations and rate limits. Coupled with a new Google Gemini Flash 2.5 powered LLM the Packet Copilot is working better than ever ! It is quite noticeably faster It is more affordable (for us) to host and provide as a community service It is more stable - no more rate limit errors due to external constraints Now it is hard to say "better" as a broad statement; but using the reasoning capable Flash 2.5 model from Google has enabled much larger context windows leading to much a larger (5Mb) file size capacity for your pcaps Using metadata filtering (dropping HEX data); coupled with the larger context windows; not only can we handle larger file sizes we can now handle even the most difficult capture and help make sense of it. Additionally with some model adjustments the AI Agent system is working incredible well! How this works is that when any public IP addresses are detected in the uploaded PCAP flows the Packet Copiliot launches AI Agents with the ability to use those public IP addresses and perform some amazing lookups to further augment the original PCAP: *NSLoookup *WhoIs *BPG Lookup of ASN info *Abuse IP check for reputation scores *Geolocation of the IP My sessions at both ONUG and SharkFest demonstrate exactly how this is achieved and the code is also open source ! What I find most interesting is that beginners and even seasoned professionals at events like Sharfest are finding creative ways to use the Packet Copilot ! What would you ask your packet ? Try it out today: packetcopilot.selector.ai

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Funding

Selector 3 total rounds

Last Round

Series B

US$ 33.0M

See more info on crunchbase