ForceN
Physical AI
Tier 1 force-torque sensing systems and edge intelligence for surgical, logistics and frontier robotics.
ForceN (formerly Forcen) supplies made-to-measure force/torque sensors and edge intelligence as a Tier 1 provider to surgical, logistics and frontier robotics customers. Its sensing stack combines ForceFilm, a digitally manufactured thin-film transducer array supporting one to six degrees of freedom; Synap, full-range calibration with on-board compensation and edge computing; and DedicatedOverload, which separates sensing range from overload to combine high sensitivity with robustness. The company claims better than 3% absolute accuracy, more than 500% reusable overload, zero recalibration and operation from -20C to 70C, with EtherCAT, Ethernet, CAN and USB interfaces. ForceN holds ISO 9001:2015 and ISO 13485:2016 certification and is Intertek-certified for force-sensing design and development.
Research mapping
Physical AI / Perception & Sensing (L7) / A
Evidence boundary
Original analysis and independent corroboration remain under development. Commercial scale and durable technical advantage remain under review.
What makes it defensible
Digitally manufactured thin-film force/torque transducers with on-board edge intelligence - made-to-measure sensing at production quality, certified to medical-device standards.
Position in the stack: Sensor supplier between the actuator and the manipulation stack, giving robots a sense of touch. The moat is a scalable thin-film manufacturing process plus ISO 13485 medical certification that robotics-only sensing competitors lack.
Who buys it
Named customers: Asensus Surgical, Agility Robotics, Pickle Robot, Amazon Robotics, Smith+Nephew, Andromeda, Robocath, Smart Robotics
Founding team
Dr. Robert Brooks — Founder and CEO — Founded ForceN (originally Forcen) in Toronto in 2019 and leads development of its force/torque sensing technology and edge intelligence
SourceFinancing detail
- Last round
- Series A
Investors: Yaletown Ventures (lead; $5.5M); existing investors Garage Capital and Reinforced Ventures
Mapped funds and investors
Direct relationships supported by published evidence.
Reported holdings as-of
No sourced relationships mapped yet.
Disclosed investment history
No sourced relationships mapped yet.
Showing up to four relationships in each group. ETF weights describe the fund’s portfolio, not ownership of this company. Private investment history does not establish current ownership.
Evidence & media
-
ForceN — robotic force-torque sensing systems
What this source supports: ForceN builds force/torque sensors plus edge intelligence (ForceFilm transducer, Synap calibration/edge compute, DedicatedOverload) for surgical, logistics, humanoid and space robotics.
What it does not establish: First-party product marketing — no shipped-unit counts, named customers, or economics.
Source -
Forcen closes $8.35M CAD to develop its touch-tech for robots
What this source supports: CAD $8.35M all-equity pre-A (closed Feb 2024) co-led by Brightspark Ventures and BDC Capital Deep Tech Venture Fund; $12.95M CAD raised to date; founder/CEO Robert Brooks.
What it does not establish: No valuation, revenue, or named customers disclosed.
Source -
Forcen closes funding to develop 'superhuman' robotic manipulation
What this source supports: CAD $8.35M (~US$6.1M) round; force/torque sensing and edge intelligence already moving into production with customers across surgical, logistics, humanoid, and space robotics.
What it does not establish: Customer names withheld; no revenue or unit volumes.
Source -
Forcen raises $8.35M to enable robotics manufacturing and research
What this source supports: Confirms round co-led by Brightspark Ventures and BDC Capital Deep Tech; Toronto-based force/torque sensing + edge intelligence.
What it does not establish: No valuation or customer disclosure.
Source -
ForceN to give a crash course on force and torque sensing for humanoids at RoboBusiness
What this source supports: P2 press coverage; CEO Robert Brooks session at RoboBusiness 2026 (Oct 20-21, Santa Clara). published_at = retrieval-date fallback (article date not machine-readable).
Source