INTERA Innovations Newsletter
Edition: January 2026 | Issue #1 IMPROVING THE INNOVATION PROCESS
Dear readers,
INTERA Group announces the launch of the FALCON our first AI Accelerator solution; FALCON EDGE AI represents a groundbreaking leap in hardware designed to supercharge AI training and inference at unprecedented speeds and efficiencies.
Why This Matters
As AI models grow more powerful, the demand for specialized hardware has never been greater. Traditional GPUs, while versatile, were not built for the unique workloads of modern AI. Our new FALCON AI Accelerator is purpose engineered from the ground up to:
- Accelerates training of massive models by up to 10x compared to leading alternatives
- Reduces energy consumption by 60% per FLOPS
- Scales seamlessly across clusters of thousands of chips with ultra-low latency interconnects
- Supports mixed-precision workloads natively (FP8, FP16, BF16, INT8)
FALCON by INTERA isn’t just another AI accelerator, it’s the foundation for the next era of AI.
Built for the Future of AI

Now Available for Early Access Clients and Partners
We’re opening a limited early access program for select research partners, EDGE solution providers, hardware developers, and enterprise AI teams.
Successful applicants will receive:
- Priority access to our FALCON Development Kits (SDK)
- Direct support from INTERA’s AI specialist silicon and systems teams
- Co-design opportunities for next-gen workloads
The Road Ahead
This is just the beginning. INTERA´s FALCON AI Accelerator Chip is the first in a family of silicon optimized for scale models and beyond. Future generations will push efficiency, scale, and integration even further, all while remaining fully open for the research community. INTERA is not just developing EDGE AI accelerated hardware. We’re building solutions to help our customers improve their innovation.
Thank you for being part of this journey.
The INTERA EDGE AI Team
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Forward-looking statements reflect current expectations but are subject to risks and uncertainties that may cause actual results to differ materially.
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