{"id":77998,"date":"2026-06-18T06:47:25","date_gmt":"2026-06-18T06:47:25","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/77998\/"},"modified":"2026-06-18T06:47:25","modified_gmt":"2026-06-18T06:47:25","slug":"sima-launches-agentic-development-environment-for-physical-ai","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/77998\/","title":{"rendered":"SiMa Launches Agentic Development Environment for Physical AI"},"content":{"rendered":"

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Edge AI chip company SiMa.ai has launched an agentic development environment designed for developers of physical AI systems working with the company\u2019s Modalix MLSoC chip<\/a>. Part of the company\u2019s Palette SDK, Palette Neat, combines an execution library and an agentic workflow to speed up development time for robots, drones, healthcare, and industrial automation.<\/p>\n

Developers can design systems in plain English and develop in days, sometimes hours, SiMa CEO Krishna Rangasayee told EE Times.<\/p>\n

\u201cTo build a great silicon company, you need to have amazing software,\u201d he said. \u201cOur industry, unlike the data center market, is not really the most proficient in AI. The more we can abstract access to the technology and the more we can make it a push-button experience, the better the AI experience will scale.\u201d<\/p>\n

SiMa aims to solve the embedded AI industry\u2019s problems by allowing data from any sensor modality to run any AI model efficiently. A developer might prompt the agent with basic information about the system, its sensors, and constraints such as accuracy and latency, and the agent can design a SiMa-based AI system accordingly.<\/p>\n

\t\t\t\t\t\"Built-In<\/a><\/p>\n

By Morten Block, Global Eng. Director, Segments and Technology go-to-market\u00a0 06.17.2026<\/p>\n

\t\t\t\t\t\"YMIN<\/a><\/p>\n

By Shanghai Yongming Electronic Co.,Ltd\u00a0 06.16.2026<\/p>\n

\t\t\t\t\t\"How<\/a><\/p>\n

By Vibheesh Bharathan, Director, Head of PSOC\u2122 Multi-Sense MCUs, Infineon\u00a0 06.15.2026<\/p>\n

\t\t\"KrishnaKrishna Rangasayee (Source: SiMa)<\/p>\n

SiMa\u2019s Modalix hardware is a heterogeneous compute platform\u2014an SoC with Arm CPUs and an in-house NPU. Physical AI is, in some ways, more complicated than cloud AI, since developers are dealing with \u201creal-world challenges,\u201d such as front-end logic, sensor integration, data parsing, different data types requiring pre- and post-processing, and more. Writing code for this can take 6-12 weeks in a typical customer team, Rangasayee said. \u00a0<\/p>\n

\u201cIf your software is poor, which unfortunately is the norm across the industry, sometimes it takes months to iterate around this,\u201d he said. \u201cWe\u2019re dismantling this barrier with Neat.\u201d<\/p>\n

The new agentic workflow can condense weeks of effort into days or hours, drastically improving AI\u2019s accessibility, Rangasayee said.<\/p>\n

\u201cWe have been so focused on numbers and speeds in the industry, but the maturity I see across customers is: All of that is great, but can you get me to production quickly?\u201d he said. \u201cCan you reduce the friction [to transition] from my investment in a GPU or DSP company and make it a SiMa product, and how quickly can you do it?\u201d<\/p>\n

SiMa is engaged with all automotive OEMs through its partnership with Synopsys<\/a>, Rangasayee said. SiMa\u2019s AI hardware IP and its toolchain are fully integrated into Synopsys\u2019 architecture evaluation platform, simulation, and emulation environments to enable decisions, such as buying SiMa chiplets or licensing IP. Automotive customers have been impressed with Palette Neat\u2019s capabilities, he said.<\/p>\n

SiMa shipped around 1,000 units of its production-qualified SoM last year, and around 20 customers have already engaged with Palette Neat in the run-up to general availability, Rangasayee said.<\/p>\n

\"SiMa'sSiMa\u2019s SoM is pin-compatible with the Nvidia Jetson Orin. (Source: SiMa)Code conversion<\/p>\n

SiMa\u2019s agents can convert existing code to run on SiMa hardware. Models such as Claude and Codex have been trained extensively on Nvidia Cuda kernels, and starting from code rather than from scratch can be effective, as it allows testing for equivalency, Manuel L\u00f3pez Rold\u00e1n, software product manager at SiMa, told EE Times.<\/p>\n

\"ManuelManuel L\u00f3pez Rold\u00e1n (Source: SiMa)<\/p>\n

\u201cIt isn\u2019t recompiling code, it\u2019s more like what a human would do\u2014analyze what the Cuda code is doing, then figure out the best way of doing that mathematical operation with SiMa,\u201d he said.<\/p>\n

Agents can also create better code than humans can write in many cases, Rangasayee said, since they iteratively go through every option to optimize fully. This will go some way toward bridging Cuda\u2019s perceived moat, he added.<\/p>\n

\u201cEverybody now has access to the most expert engineering team you could get hold of, but you still stay at the abstraction layer, the simplicity, of just describing a problem in English and let the system really work for you,\u201d he said.<\/p>\n

There is a difference between using agents to solve the problem versus letting agents solve it while retaining control, Rangasayee said.<\/p>\n

\u201cWe are not reliant on some ethereal [thing] to go and do things which we worry about whether they did it right or not,\u201d he said. \u201cWe know what we are doing. We are instructing it to do it to the degree and comfort and accuracy, and testing that we want. And we have trained it with skills so that it always lives up to our quality standards.\u201d<\/p>\n

Agentic AI has come a long way in the last six months, Rangasayee said, and is \u201crobust,\u201d with trust improving.<\/p>\n

SiMa\u2019s existing Palette SDK will maintain access to the lower-level software toolchains for experienced developers, Rangasayee said.<\/p>\n

\u201cPeople have a somewhat euphemistic view that it\u2019s somehow magic to work with Claude or Codex, and everything is magic,\u201d he said. \u201cBut the secret sauce is we understand our architecture really well. We understand how to orchestrate things better than anybody else. And we are deploying agents to do the orchestration for us instead of human beings.\u201d<\/p>\n

See also:<\/p>\n

SiMa.ai\u2019s Second-Gen Edge AI Chip Goes Multi-Modal<\/a><\/p>\n

Synopsys Collaborates with SiMa.ai on Automotive AI IP<\/a><\/p>\n

Sima.ai CEO: Software Is The Company<\/a><\/p>\n

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AGENTIC AI<\/a>, AI AND BIG DATA<\/a>, BIG DATA<\/a>, PHYSICAL AI<\/a>, ROBOTICS<\/a>\n <\/p>\n

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NVIDIA<\/a>, SIMA.AI<\/a>\n <\/p>\n","protected":false},"excerpt":{"rendered":"\/\/php echo do_shortcode(‘[responsivevoice_button voice=”US English Male” buttontext=”Listen to Post”]’) ?> Edge AI chip company SiMa.ai has launched an…\n","protected":false},"author":2,"featured_media":77999,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[179,7493,35898,3845,708,377],"class_list":["post-77998","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-agentic-ai","tag-agentic-artificial-intelligence","tag-ai-and-big-data","tag-big-data","tag-physical-ai","tag-robotics"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/77998","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=77998"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/77998\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/77999"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=77998"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=77998"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=77998"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}