Tensordyne (formerly Recogni)
Sunnyvale, US Β· 8 known investors
Tensordyne builds AI hardware, chips, and software systems optimized for efficient inference at reduced energy and computational cost. The company serves organizations seeking advanced AI capabilities with simplified deployment and lower operational overhead.
Also known as Recogni Β· Tensordyne
Founders & leadership
Investors Β· 8
Company profile
researched Aug 2026Tensordyne, previously known as Recogni, develops AI inference hardware and systems built around a proprietary logarithmic-mathematics ("log-math") compute architecture. Its flagship offering is Tensordyne Napier, described by the company as a class of AI inference system combining log-math compute with a low-latency scale-up interconnect to reduce the cost and energy consumption of inference workloads. The Napier platform is presented as a set of components: TDN Math (the numerical approach), TDN AIP (the Napier chip), TDN ACT (the compute tray), and TDN LINK (the scale-up interconnect).
The company positions Napier as fully air-cooled, operating at 30 kW per pod, which it states removes the need for liquid-cooling infrastructure and allows deployment in a broad range of data centers. Stated system capabilities include 608 PFLOPS of dense compute per rack, per-user throughput above 1,000 tokens per second, real-time 4K video generation at 30 FPS, and serving of multi-trillion-parameter Mixture-of-Experts models using EP72 parallelism and TDN Link, which the company claims runs giant models at twice the speed of leading solutions. Models can be run in 16-bit precision. Software integration is offered through PyTorch, Triton and vLLM support within Kubernetes-managed stacks.
Business model
Tensordyne designs and supplies AI inference systems β chips, compute trays, interconnect and accompanying software stack β manufactured through foundry partner TSMC and offered to datacenter operators and enterprises for deployment in their own facilities.
Latest developments
Tensordyne announced Napier and reported completing tapeout of its 3nm Napier chip with Broadcom and TSMC, with silicon transitioning into high-volume manufacturing at TSMC in 2026. It also states that models such as DeepSeek-V4 and larger MoE architectures are targeted workloads.
βΈFull profile β market position, technology, go-to-market, geography, history
Market position
Tensordyne competes in datacenter AI inference silicon and systems, positioning its log-math architecture against GPU-based inference infrastructure on cost, energy efficiency and latency.
The company differentiates on logarithmic math-based compute and its scale-up interconnect, claiming higher energy efficiency than GPU architectures, air cooling instead of liquid cooling, and cited figures including 608 PFLOPS of dense rack compute, over 1,000 tokens per second per user, and 2x the speed of leading solutions on large MoE models, while retaining full 16-bit precision.
Technology
The architecture is based on logarithmic mathematics for AI compute, protected by patents first filed in 2019, combined with a low-latency, any-to-any cell-based scale-up interconnect (TDN LINK) enabling linear scaling. Napier chips are fabricated on a 3nm process with Broadcom as design partner and TSMC as foundry; the earlier Scorpio generation used a 7nm process. The system is disaggregated to reduce bottlenecks in multi-trillion-parameter model serving, air-cooled at 30 kW per pod, supports 16-bit precision inference, and integrates with PyTorch, Triton and vLLM.
Go-to-market
Direct engagement via the company website, with named product and sales contacts offering booked calls for different customer segments, and a planned technical whitepaper on the Napier system.
Hyperscalers building large-scale inference deployments; "neo cloud" providers serving high-margin, low-latency inference; enterprises running frontier models on-premises; and application-layer companies and foundation model builders.
Geography
Dual presence in North America and Europe, with a US office at 1195 Bordeaux Dr, Sunnyvale, CA 94089 and a German office at Brienner Strasse 59, Munich 80333.
History
The company filed its first five foundational patents on log-math-based architectures in 2019 and began designing Scorpio, its first-generation chip. Scorpio was taped out in 2021 with Broadcom, with functional 7nm silicon received from TSMC, validating the log-math architecture in hardware. In 2022 functional Scorpio samples shipped to initial validation customers, including a development system performing surround-view object detection. During 2023 the company extended support to transformer-based models and identified opportunities in generative AI workloads such as GPT and Stable Diffusion. In 2024 it halted its legacy vision tracks and refocused entirely on Napier, a datacenter AI inference chip, and entered a technology partnership with Juniper Networks to integrate scale-up networking components. Through 2025 the company optimized silicon, systems and software for Mixture-of-Experts models and agentic workloads, citing industry shifts such as DeepSeek-R1. In 2026 it completed tapeout of a 3nm Napier chip with Broadcom and TSMC and stated that Napier silicon was transitioning into high-volume manufacturing at TSMC.
Compiled by commissioned research from 1 cited public sources β announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed β not independently audited.
Timeline Β· 9
launches, deals, and filingsNapier silicon transitioned from development into high-volume manufacturing at TSMC facilities.
The company completed the netlist and tapeout of its 3nm Napier chip in partnership with Broadcom and TSMC, targeting multi-modal generative AI inference.
Throughout 2025 the company optimized its silicon, systems and software for Mixture-of-Experts models and agentic AI workloads.
The company halted its legacy vision product tracks and refocused engineering on Napier, a next-generation datacenter AI inference chip.
Partnership to integrate Juniper Networks scale-up networking components with the Tensordyne platform for fabric scalability in LLM clusters.
While developing its second-generation architecture, the company added support for transformer-based models and evaluated generative AI workloads such as GPT and Stable Diffusion in simulation.
Functional Scorpio samples were delivered to initial validation customers, including a development system running surround-view object detection continuously.
Scorpio was taped out with Broadcom and functional 7nm silicon was received from TSMC, validating the log-math architecture in hardware.
The company filed its first five foundational patents covering log-math-based AI compute architectures and started design of Scorpio, its first-generation chip.
Dated company events from announcements, filings, and press; legal rows summarize public dockets and regulator releases.
βΈResearch sources Β· 1
primary sources listed
- Tensordyne (formerly Recogni)tensordyne.ai Β· web
1 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Tensordyne (formerly Recogni) do?
- Tensordyne builds logarithmic-math AI inference systems, led by its air-cooled Napier datacenter platform.
- Who founded Tensordyne (formerly Recogni)?
- Tensordyne (formerly Recogni) was founded by RK Anand, Gilles Backhus, R K Anand.
- Who are Tensordyne (formerly Recogni)'s investors?
- Tensordyne (formerly Recogni)'s investors include Bosch Ventures, Dns Capital, GreatPoint Ventures, Ineffable Ventures, Linden Capital, Mayfield Fund, Robert Bosch Venture Capital, Toyota Ventures.
- Where is Tensordyne (formerly Recogni) headquartered?
- Tensordyne (formerly Recogni) is headquartered in Sunnyvale, US.


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