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UAE-based Mastiṣka announced a $10 million seed round in November 2025 to develop AI inference hardware and related software. Its proposed path starts with a custom FPGA accelerator card and later moves toward a RISC-V-based ASIC. Those are plans, not evidence of a shipping product: the available coverage provides no launch date, independent benchmarks, or named investors.
What Mastiṣka announced
EE Times reported on 25 November 2025 that Mastiṣka had raised $10 million, mainly from sovereign wealth funds in the Gulf Cooperation Council (GCC). CEO Suresh Sugumar said the funding would support data-center-class inference accelerators and a UAE-based fabless semiconductor company using open-source technologies. The report did not identify the funds by name. EE Times’ report is the detailed source for the announcement and the company’s plans.
A report from Startup Researcher, published two days later, also described the seed round and sovereign-hardware plans. Wamda search results echoed the broad announcement, though its article page was not accessible in the reporting reviewed.
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What the proposed first accelerator would do
FPGA card for data-center inference
The first product Mastiṣka described is a custom PCIe FPGA card loaded with its own IP, based on Altera Agilex-7M and intended to support up to 96 GB of HBM. Sugumar said the cards were intended for commercial deployment rather than prototyping alone. The November 2025 report did not give a price, shipment date, or independently verified specification.
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- ✅Enabling real-time, low latency and high-efficiency AI inferencing on the edge devices
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- ✅Supports Linux and Windows. Supports the temperature range of -40°C to 85°C
For context, EE Times cited 32 GB HBM for Altera’s own Agilex-7M cards. That comparison concerns stated memory capacity only; it does not establish that Mastiṣka’s planned card would be faster, cheaper, more efficient, or otherwise superior.
Early demonstration and what it does—and does not—show
EE Times reported that a Mastiṣka FPGA demonstration ran DeepSeek-7B “pretty slowly.” Sugumar described a possible tradeoff: a workload that might otherwise use GPUs could require more FPGAs and rack space. The report supplied no measurements or reproducible comparison, so it cannot establish throughput, energy use, cost, or a performance advantage.
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The longer-term RISC-V chip roadmap
After the FPGA phase, Mastiṣka described a RISC-V-based ASIC using a neuromorphic-inspired digital approach centered on parallelization. Sugumar said in November 2025 that the company aimed to tape out the chip in roughly three years, allowing time for its IP to mature. This was a forward-looking target, not confirmation that a tape-out has occurred or that a delivery date is assured.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsThe company also said it was developing brain-inspired models, including modified transformers, while its software team worked toward CUDA compatibility. The reporting does not establish that CUDA compatibility is complete, or demonstrate model performance or energy efficiency.
What “sovereign AI” means in Mastiṣka’s pitch
Sugumar’s argument is that sovereign AI requires control of silicon as well as data. He said sovereign customers would receive full access to audit the design for cybersecurity purposes. This is the company’s stated proposition; the report does not independently verify the audit process, its scope, or any security outcome.
The CEO identified potential markets in other GCC countries, Southeast Asia—including India—and wider BRICS and Global South markets. He said Mastiṣka was not targeting the United States or China, which he characterized as having their own competitive sovereign chip programs. These are intended markets, not disclosed customers or signed contracts.
Rank #4
- ✅Powered by 26 Tera-Operations Per Second (TOPS) Hailo-8 AI Processor. 2.5W typical power consumption
- ✅Scalable, enabling simultaneous processing of multi-streams & multi-models
- ✅Enabling real-time, low latency and high-efficiency AI inferencing on the edge devices
- ✅Supports TensorFlow, TensorFlow Lite, ONNX, Keras, Pytorch frameworks
- ✅Supports Linux and Windows. Supports the temperature range of -40°C to 85°C
Funding, team, and expected revenue
EE Times reported that Mastiṣka had around 40 people at the time: a model-creation team in Abu Dhabi and a VLSI team in India. Startup Researcher reported that the company was founded in 2024. These details describe reporting from November 2025, not a verified current headcount or office map.
Sugumar said one investor required the company to establish a 60-person office in a GCC country; the report did not name the investor or country. He also expected FPGA-based servers to generate revenue while the chip design matured. That is a forecast, not evidence that sales or revenue have begun.
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How to assess the announcement
The announcement establishes a funding round and a stated technology roadmap, but leaves key buyer questions unanswered. The reporting provides no independent performance results, benchmark methodology, product availability, pricing, or confirmed customers. Anyone evaluating the plan should distinguish stated specifications and targets from demonstrated capabilities.
- Performance: no reproducible workload results or direct GPU comparison are reported.
- Capacity and system fit: up to 96 GB HBM is a planned card configuration; rack-space and system requirements are not quantified.
- Software: CUDA compatibility is a stated mission, not a reported completed capability.
- Control and security: audit access is part of the company’s pitch, with no independently validated security outcome described.
- Maturity: the FPGA card is planned, and the ASIC tape-out timing is an aim stated in November 2025.
In short, Mastiṣka is positioning itself as a UAE-based effort to build sovereign inference hardware, with FPGA-based servers as a nearer-term commercial route and a RISC-V ASIC as a longer-term ambition. The available reporting supports describing the strategy and funding, not claiming that the company has already delivered a competitive accelerator.
Quick Recap
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