SmartGateVC

Today we're adding video_frames: send Mk1 the frames you've already decoded on the client, each with its own timestamp. The model sees exactly the frames you send.

Today, we're announcing our $15 million Series A, led by @a16z. In 2018, @tmartiro , @ars_arakelyan , and I started @netris_io . The hyperscalers had proven what's possible when you automate the network at scale, but it took custom tooling and armies of engineers. We wanted to put the same technology within reach of any operator. For eight years, we built very complex technology that automates the hardest part of any cloud, the network. Our vision was ahead of its time. At the early stages, most investors and most of the industry didn't believe in what we were building. Then, it started working. Tier 2/3 cloud operators and service providers began choosing @netris_io to automate their networks, proving our bet was right. Then AI infrastructure arrived. GPU clusters require dynamic configuration and automated management of multiple networks at once — East-West, OOB, North-South, scale-up, host, and edge networking, involving multiple technologies – Ethernet, InfiniBand, NVL72, DPUs, SuperNICs, RDMA, RoCE, XDP, and others — none of which were designed to work together in concert. Networking became the hardest problem in AI infrastructure, and it was at a scale and complexity no one had seen before. And it was the exact problem we had spent years solving. We worked closely with @nvidia and other partners to build automation and multi-tenancy across all AI network fabrics. We built an ecosystem of partners around the platform — compute orchestration software vendors that, together with Netris, give GPU cluster operators everything they need to launch, operate, and monetize GPU clouds. Thanks: @nvidia , @HPE , Rafay, @vclusterlabs , @RedHat , @MirantisIT , and all amazing partners The results followed. Netris has become an essential network automation and multi-tenancy layer for AI infrastructure. Over the last 12 months, Netris grew its ARR 800% and surpassed 35 live AI cluster deployments — more than all other network automation vendors combined. Today, many of the world's largest AI clouds, sovereign AI operators, and AI factories run on Netris. None of this would have happened without my co-founders Tigran Martirosyan and Arsen Arakelyan, the early founding team members, Armen Hovhannisyan, Gor Poghosyan, Artashes Balabekyan, and the entire Netris team. Big thanks to Leon Ariyan, @SkyDeck_Cal , @SmartGateVC , @GranatusVC , and all early Netris investors. And huge thanks to all our customers! We're excited to welcome @appenz to our Board of Directors. I'm excited to have him, along with fellow a16z partners @martin_casado and @RaghuRaghuram, on our side. At Nicira, VMware / NSX, and BigSwitch Networks, they helped build the networking layer that defined the modern data center. Netris is doing the same for AI. The AI buildout is still in its early days. We’re seeing 10-100K GPU clusters among our customers. Their scale, demands, and complexity are growing quarterly — and that's exactly what we built Netris for. We're just getting started.

Netris has raised its $15 million Series A, led by @a16z. Guido Appenzeller (@appenz) led the round and is joining our board, with fellow a16z partners Martin Casado (@martin_casado) and Raghu Raghuram (@RaghuRaghuram) behind the investment. Together, they're the team behind the network virtualization that reshaped the modern data center — Nicira, NSX, VMware. They solved networking for the data center. Netris is doing it for AI. Eight years ago, that bet looked wrong. We believed the network would become the hardest problem in computing, and that nobody outside the hyperscalers had the tools to solve it. The hyperscalers had built that automation for themselves — armies of engineers, custom systems. Everyone else was stuck. So we built a platform to put it within reach of any operator. Most investors didn't see it. Most of the industry didn't either. But the operators actually running networks did — they started choosing Netris long before AI was on anyone's roadmap. Then the AI buildout hit, and the network became the bottleneck for the entire industry. A single GPU cluster runs across multiple network fabrics at once — Ethernet, InfiniBand, NVL72 — each with its own control plane, spanning hundreds or thousands of switches. None of it was built to work as one, and the automation tools that came before were never designed for it. One misconfiguration can take an entire cluster down. It was the exact problem we'd spent years solving — and the platform was already built for it. Netris automates network operations across every fabric and delivers true multi-tenancy through hard isolation (enforced on networking hardware). Operators can now run shared GPU clouds, maximize GPU utilization, and provision new tenants instantly. In the last 12 months, Netris experienced 800% ARR growth and reached 35+ live deployments and growing — more live deployments than all other network automation vendors combined. The largest AI clouds in the world have chosen Netris: neoclouds, sovereign AI operators, and AI factories. Huge thanks to the Netris team, our customers, investors, @nvidia, and our ecosystem partners, including @MirantisIT, @rafaysystemsinc, @RedHat, @spectrocloudinc, @vclusterlabs, and @HPE. The AI buildout is just beginning. Netris has been ready for this for eight years. Read the press release: netris.io/blog/andreesse…

Netris is headed to @RaiseSummit in Paris, July 7–9. Over the last 12 months, #Netris has gone live with 35+ AI cloud deployments across neoclouds, sovereign AI operators, and AI factories worldwide. Building AI infrastructure requires significant upfront capital, and investors expect returns on a tight timeline — yet networking remains the primary bottleneck between GPU investment and revenue. At #RAISESummit, we will be talking with AI operators about how to solve these challenges with #Netris #NAAM: Network Automation, Abstraction, and Multi-Tenancy. There are multiple ways to engage with us at RAISE Summit: visit booth #32A, attend our speaking sessions, and register to attend our hosted events. SPEAKING SESSIONS 🌟Session: Network Automation Lessons Learned from Launching 35+ Multi-Tenant Clouds and AI Factories 🗓️Thursday, July 9, 12:20 PM, Grace Hopper Stage ▪️Alex Saroyan, CEO and Co-founder, @netris_io 🌟Panel: Powering AI Infrastructure: Solving the 21st Century Manhattan Project 🗓️Thursday, July 9, 1:20 PM, Master Stage ▪️Alex Saroyan, CEO and Co-founder, @netris_io ▪️Vik Malyala, Chief Business Officer, @Supermicro ▪️Ben Richardson, VP of Strategy, @CoreWeave ▪️Shaun O'Meara, CTO, @MirantisIT ▪️June Paik, CEO, @FirassaAI ▪️Jeremie Eliahou Ontiveros, Managing Director, @SemiAnalysis_ VIP EVENTS 🌟Executive Reception by #Netris and @vcluster 🗓️ Wednesday, July 8, 7:00–10:00 PM 🔹Register to attend: luma.com/vcluster-fvdd 🌟Executive Breakfast by #Netris with @RedHat 🗓️Thursday, July 9, 7:30–10:00 AM 🔹Register to attend: luma.com/lkaj7i2v 📍BOOTH #32A Get a Netris demo at Booth #32A or reserve a meeting at: netris.io/events/raise-s…

It's not what you know about QE and APE, it's what you do know that ain't so. GenAI in Localization, we're busting myths about QE and APE — AI to check and fix AI translations. Join us on Thursday! modelfront.com/events/genai-i…

Today we're releasing the Perceptron Files API to make building on top of our models easier. Upload an image or video once, reference it by id across every request thereafter.

Reasoning in visual content remains an open problem - we are sharing our first study on formalizing visual reasoning. In this blog we walk through reasoning capabilities (backtracking and spatial grounding) in a case study of visual games (Set!).

Today we're releasing Perceptron Agentic Detection: localize anything you can describe in natural language or show examples of.

Really excited to see that the project I’m leading, which we officially released four days ago, just got its first 1K GitHub stars, with 300+ gained in the last 24 hours. It also reached #2 Repository of the Day on GitHub. Really proud to be building this with @KamoAghbalyan, @khustup, @DBuniatyan, and the rest of the team.

Big news for Async text-to-speech! Async Flash v1.5 just landed in the most attractive quadrant on Artificial Analysis’ Quality vs. Price benchmark with the best quality score among models under $10 per 1M characters 💪🏻🏆 That means Async now gives creators one of the strongest quality-to-price ratios in the TTS market, ahead of ElevenLabs, MiniMax, Microsoft, and OpenAI. High-quality AI voice is no longer a premium-only feature. It’s already inside Async. #AIVoice #VoiceAI #TextToSpeech #TTS #Async

Coding agents that actually get better the more your team uses them. Introducing Hivemind: continual learning for AI coding agents. Hivemind turns the traces from every agent your team runs (Claude Code, Codex, Cursor, Hermes, OpenClaw, Pi) into reusable skills, then pushes those skills across all of them. All on your cloud storage. Now with SkillOpt built in, your skills get trained: +19.1 points of accuracy in Claude Code, +24.8 in Codex, best or tied on all 52 setups tested. Open source, one line install.

Already powering Daily, Vapi, LiveKit, Vodex, Ultravox and the world's largest AI labs. The next generation of voice agents won't just talk. They'll listen. Available now → krisp.ai/blog/viva-2-0-…

Today we're releasing Perceptron Mk1: frontier video and embodied reasoning.

@modelfront @bittlingmayer @slatornews @DeepLcom @krispHQ Go @modelfront and @krispHQ !

The new 2026 @slatornews Index is out! The tech category features ModelFront as the leader in quality prediction and automatic post-editing, alongside @DeepLcom in traditional translation AI, and @krispHQ in voice. Large buyers use ModelFront to scale translation while keeping human quality.  Over 1B words of Fortune 500 content were processed with ModelFront in 2025. Read more at modelfront.com/news/slator-in…

Deeplake now is GPU pilled. Excited to announce The GPU Database!

Introducing Accent Conversion SDK for desktop, mobile and server deployment. 🚀 We’re bringing our industry-leading, real-time Accent Conversion technology to developers 🧵

The Genesis Mission calls for new ways to accelerate scientific discovery. This is our contribution Multimodal search across 25M papers is a step toward science discovery that moves at the speed of curiosity. Releasing, - Visually indexed scientific paper dataset with open access 25M papers, 450M+ visually indexed pages. Total 175TB+. All on Deep Lake - Open-source scientific data agent that achieves 48% SOTA on Humanity's Last Exam with tools including the indexed scientific research dataset. Excited to see what discoveries you all uncover with this. Try it and share your most interesting findings.

🔥 Fireside Chat live now! @modelfront's Adam Bittlingmayer joins Slator's @florianfas for a deep dive into #translation #AI, QE, and how enterprises are deploying the next wave of language tech. #SlatorConRemote #SCRemoteDec25 @bittlingmayer

🚨 Isaac 0.1 from @perceptroninc is now live on Replicate. It's a lightweight, grounded vision-language model that excels at OCR, spatial reasoning, and visual question answering. Read more here: replicate.com/blog/isaac-01