• Skip to main content
  • Skip to secondary menu
  • Skip to footer

Technologies.org

Technology Trends: Follow the Money

  • Technology Events 2026-2027
  • Sponsored Post
  • Technology Markets
  • About
    • GDPR
  • Contact

AIStorm Raises $13.2M to Bring Real-Time AI-in-Sensor Technology to the Edge at a Fraction of the Cost

February 11, 2019 By admin

AIStorm, an innovator of high-performance AI-in-sensor processors, has closed $13.2 million in Series A financing from Egis Technology Inc., a major biometrics supplier to handsets, gaming, and advanced driver-assistance systems (ADAS); TowerJazz, the global specialty foundry leader that specializes in image sensors for commercial, industrial, AR, and medical markets; Meyer Corporation, a world leader in food preparation equipment; and Linear Dimensions Semiconductor Inc., a leader in biometric authentication and digital health products.

Team of experienced semiconductor executives, backed by leading sensor and equipment manufacturers, aims to equip the next generation of handsets, IoT devices, wearables, and vehicles with a new approach to AI processing at the edge; compared with edge GPU solutions, AIStorm’s technology boosts performance while lowering power requirements and system cost

“This investment will help us accelerate our engineering & go-to-market efforts to bring a new type of machine learning to the edge. AIStorm’s revolutionary approach allows implementation of edge solutions in lower-cost analog technologies. The result is a cost savings of five to ten times compared to GPUs — without any compromise in performance,” said David Schie, CEO of AIStorm.

Using sensor data directly—without digitization—enables real-time processing at the edge

The semiconductor industry is striving to process sensor information at the edge to reduce the cost and security risk associated with transmitting large amounts of raw data from edge sensors. AI systems require information be available in digital form before they can process data, but sensor data is analog. Processing this digital information requires advanced and costly GPUs that are not suitable for mobile devices: they require continuous digitization of input data, which consumes significant power and introduces unavoidable digitization delay (latency). AIStorm aims to solve these problems by processing sensor data directly in its native analog form, in real time.

“The reaction time saved by AIStorm’s approach can mean the difference between an advanced driver-assistance system detecting an object and safely stopping versus a lethal collision,” said Russell Ellwanger, CEO of TowerJazz.

“Edge applications must process huge amounts of data generated by sensors. Digitizing that data takes time, which means that these applications don’t have time to intelligently select data from the sensor data stream, and instead have to collect volumes of data and process it later. For the first time, AIStorm’s approach allows us to intelligently prune data from the sensor stream in real time and keep up with the massive sensor input tasks,” said Todd Lin, COO of Egis Technology Inc.

“It makes sense to combine the AI processing with the imager and skip the costly digitization process. For our customers, this will open up new possibilities in smart, event-driven operation and high-speed processing at the edge,” said Dr. Avi Strum, SVP/GM of the sensors business unit of TowerJazz.

AIStorm’s management includes CEO David Schie, a former senior executive at Maxim, Micrel and Semtech; CFO Robert Barker, formerly with Micrel and WSI; Andreas Sibrai, formerly with Maxim and Toshiba; and Cesar Matias, founder of ARM’s Budapest design center.

About AIStorm
AIStorm is the pioneer and leader in AI-in-Sensor processing, which eliminates the latency, power and cost associated with digital GPU-based implementations at the edge. AIStorm is headquartered in Silicon Valley, with offices in Phoenix & Graz, Austria. The team includes industry veterans responsible for development of thousands of products, as well as for P&L and significant revenue growth at leading semiconductor companies. For more information, visit https://aistorm.ai.

Filed Under: Tech

Footer

Recent Posts

  • AltSql: An Embedded Database Engine That Syncs Devices and Gateways Without Conflicts
  • VPN Works: Uses Linux Network Namespaces to Isolate and Log Every Connection From an Agent
  • Precomputing: Materializes Dashboard Answers With SQLite Triggers as Data Arrives
  • Preconfiguration: Generates Reproducible Setup Across Multiple Cloud Platforms From One Spec
  • BareProxy: A Go Reverse Proxy That Makes Routing Decisions Explainable
  • AI Infrastructure Moves Beyond GPUs as Billions Flow Into Interconnects, Cloud, Robotics and Agent Systems
  • Supermicro Is Now Shipping NVIDIA Vera Rubin NVL72 Racks, With 1,152-GPU Scalable Units Ready to Order
  • Synopsys and TSMC Certify A14 Design Flows and Roll Out Agentic AI Chip Design Tools
  • Bird.com Secures $450M in Debt Financing and Opens Its Messaging Network to AI Agents
  • Meta AI Glasses Become the First Consumer Device to Record Dolby Atmos Audio

Media Partners

  • Market Analysis
  • BareProxy.com
  • App Coding
Small Infrastructure Primitives Run the $700 Billion AI Buildout, and Open Source Is How They Get Adopted
Screening Startup and Product Ideas After a Brainstorm: Four Questions, Money First
An AI Lab Is Paying Up Front for Atlas Energy’s (AESI) Generators as Agentic AI Multiplies Token Demand
Oracle’s Force Majeure Notice on Project Jupiter Shows Where AI Data Center Risk Is Landing
AI Infrastructure Credit Costs Rise as CoreWeave-Tied Bonds Price at 9.25% and China Chipmaker Profits Jump 620%
OpenAI and Anthropic Cut AI Model Prices as $1.75B in Funding Flows to Data, Security and Infrastructure
Semiconductor Revenue Hits Record $425B in Q2 2026, but Omdia’s $500B Q3 Forecast Implies Growth Halves
AI Extinction Warnings Went Global in Six Days. Nothing in the Technology Changed.
Anthropic Walks Away From $6 Billion Decart Acquisition: The Deal Was About Inference Cost, Not World Models
VR Status Report 2026: Quest Sales Keep Falling While Smart Glasses Take the Money
BareProxy 0.1 Alpha Adds Plan, Apply and Rollback
Introducing BareProxy, the Web Server and Reverse Proxy That Explains Itself
BareProxy Serves Hugo and Other Static Sites Straight From a Folder
How BareProxy Plan Shows What a Config Change Will Do Before It Goes Live
One Record per Request: How BareProxy Tracing Works
BareProxy Modules: Eight Add-Ons Around a Bare Core
Why BareProxy Routes on the Same Path It Forwards
About
Config Reference
Contact
A Background Job Queue in One SQLite File Covers What Most Apps Deploy Redis For
A Database Where Every Value Remembers Its Source, Confidence and Extraction Time
A Feature Store Small Enough to Embed: Point-in-Time Reads for Local and Edge ML
A Schema Diff That Warns Which Migration Will Lock a 40-Million-Row Table or Lose Data
A Single-File Log Database: Pipe Logs In, Query Them With SQL, Hand the File to Anyone
A Telemetry Database That Forgets on Purpose Keeps Rollups and Anomalies Instead of Raw Rows
A Tiny SQL Engine for JSON Streams Fits Between jq and a Stream Processing Cluster
An Embedded Sketch Database: Billions of Events, Megabytes of Storage, Error Bars on Every Answer
An Embedded Workflow Engine With Five Primitives: Trigger, Condition, Action, Wait and Retry
An Evidence Graph Built From Extracted Claims Keeps Contradictions Attached to Their Sources

Media Partners

  • AltSql.com
  • Technology Conferences
  • API Coding
AltSql Is a Native Hybrid of Key-Value and SQL, From the Sensor to the Gateway
AltSql Core and AltSql DB Are Now Open Source Under the Apache License 2.0
Introduction
AltSql DB 0.3 Adds Secondary Indexes and Statement Savepoints: A Lookup on a Million Rows Ran 198 Times Faster Than a Full Scan
How It Works
AltSql DB 0.2: SQL and Direct Calls Wrote Byte-Identical Files Over 100,000 Random Steps
AltSql DB Keeps a Whole Fleet in One File and Reads by Key 5 Times Faster Than SQLite Through SQL
AltSql Core and Six Prototypes Built Around It
AltSql Ask Puts One SQL Question to 500 Simulated Machines and Brings Back Only the Answers
Machine Monitoring Case Study: Overheat Alarm Handled on the Sensor While Wi-Fi Was Down
Sohn London Investment Conference 2026, November 18, London Marriott Grosvenor Square, London
SuperReturn Secondaries North America 2026, November 17–18, Convene 360 Madison, New York
Singapore FinTech Festival 2026, November 17–20, Singapore Expo, Singapore
SuperReturn Europe 2026, November 3–6, Hotel Okura, Amsterdam
Hong Kong FinTech Week x StartmeupHK 2026, November 2–6, Hong Kong Convention and Exhibition Centre, Hong Kong
Future Investment Initiative 2026, October 26–29, Riyadh
Money20/20 USA 2026, October 18–21, The Venetian Expo, Las Vegas
Sohn San Francisco Investment Conference 2026, October 13, San Francisco
Bloomberg New Economy Forum 2026, October 13–15, New Delhi
Milken Institute Asia Summit 2026, October 7–9, Four Seasons Hotel, Singapore
A Tiny ETL Binary Competes With curl, jq and SQLite in a Cron Job, So Build It That Small
An AI Agent Flight Recorder Belongs in One Portable File, the Way HAR Did It for HTTP
Benchmarking MCP Servers and Stateful API Workflows: Latency, Throughput and Tokens per Call
Diagnose a Slow API From One Request: DNS, Connect, TLS, Server Wait and Transfer
Finding API Endpoints, Tables and Flags Nobody Uses Takes Code and Traffic Together
Fuzzing MCP Servers: Generate Bad Arguments From the Tool Schema and Watch What Breaks
Give Any API a History: Poll It, Hash It and Query Old Versions With SQL
Infer Your API's Real Contract From Traffic, Then Diff It Against the Docs
Keeping Third-Party API Responses in SQLite Gets You a Cache, an Offline Mode and a History
LLM Response Caching Pays Off in CI, Evals and Agent Retries, Not in Chat

Copyright © 2026 Technologies.org

Media Partners: Market Analysis · Market Research · Referently · Photography