Frontier Research & Applied AI

Where hard problems
meet rigorous science.

Cadence Labs is a research and applied AI company building the foundational intelligence layer for hardware, robotics, IoT, and next-generation frontier systems.

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IoT Systems
Hardware Intelligence
Robotics & Embodied AI
Chip Architecture
Edge Computing
Frontier AI Models
LLM Fine-Tuning
Sensor Fusion
Neuromorphic Computing
AI Observability
Real-Time Inference
Autonomous Systems
IoT Systems
Hardware Intelligence
Robotics & Embodied AI
Chip Architecture
Edge Computing
Frontier AI Models
LLM Fine-Tuning
Sensor Fusion
Neuromorphic Computing
AI Observability
Real-Time Inference
Autonomous Systems
Research Domains

Six principles of frontier inquiry.

We work at the intersection of physical and digital intelligence — where bytes meet atoms.

01
🌐

Internet of Things

Building scaleable intelligence layers for connected device ecosystems. From sensor mesh networks to distributed edge inference, we develop the protocols and models that make billions of devices smarter.

Edge AIMQTT Mesh NetworksTinyML
02
⚙️

Hardware & Silicon

Custom chip design and AI hardware acceleration research. We explore neuromorphic architectures, in-memory computing, and purpose-built silicon for next-generation inference workloads.

VLSIRISC-V NPU DesignFPGA
03
🤖

Robotics & Embodied AI

End-to-end intelligence for physical systems. Perception, planning, and execution pipelines that let robots understand and act in complex real-world environments with minimal human oversight.

ROS2RL Sim-to-RealSLAM
04
💾

Chip & Architecture

The future of compute is domain-specific. We research memory hierarchies, dataflow architectures, and photonic computing that will power the next decade of AI workloads at scale and efficiency.

NeuromorphicPhotonic 3D StackingPIM
05
🔬

Frontier AI & LLMs

Foundational model research with a bias toward deployment. We develop fine-tuning methodologies, RLHF frameworks, and efficient inference techniques for domain-specific AI applications.

Fine-TuningRLHF RAGQuantization
06
📡

AI Systems & Observability

The reliability science of AI in production. Our flagship product SEER emerged from this research — building the tooling and methodologies that make AI systems trustworthy at scale.

MLOpsEvals MonitoringSEER
Our Approach

Research that ships.

We refuse the false choice between rigorous science and useful product. Every research thread ends in something deployable.

01

Deep Problem Identification

We spend significant time upstream — mapping failure modes in existing systems, interviewing practitioners, and identifying the root constraints that have blocked progress. The question matters as much as the answer.

02

Cross-Domain Synthesis

Hardware problems inform software solutions. AI techniques unlock new hardware possibilities. We deliberately work across the full stack — from transistors to tokens — because breakthroughs live at the intersections.

03

Prototype to Production

Every research thread has a deployment target. We don't publish and wait — we instrument, ship, measure, and iterate. Our academic rigour is in service of real-world impact, not citation counts.

04

Open Collaboration

We partner with universities, hardware manufacturers, and early-stage companies to accelerate the work. Cadence Labs is a platform for frontier builders, not an ivory tower.

6
Research Domains
1
Flagship Product
Open Problems
Now
Hiring

Actively accepting research partnerships, collaborations, and early-access pilot programmes across all six domains.

Products

Research made real.

Our product portfolio is a direct expression of our research — tools we built because nothing good enough existed.

Flagship Product
SEER

One API. Complete AI Clarity.

Born from our AI Systems & Observability research, SEER is a single API that gives any AI-powered product complete observability, automated quality evaluation, and prescriptive intelligence — replacing 4–6 fragmented tools with one clean integration.

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In Research
Kàkàņfò

Inference at the boundary.

A lightweight inference runtime optimised for heterogeneous edge hardware — ARM, RISC-V, and custom NPUs. Enables real-time ML at the device layer without cloud dependency, built for IoT and robotics deployments where connectivity cannot be assumed.

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Principles

What we stand for.

🎯

Radical Focus

We work on fewer problems, more deeply. Shallow breadth produces shallow answers. We go to the bedrock.

🔓

Open Science

Where we can, we publish. The hardest problems get solved faster when the best minds can engage with the full picture.

Bias to Ship

A working prototype in the world teaches you things a perfect paper never can. We ship early and learn fast.

🌍

Systems Thinking

Technology problems are social, economic, and physical problems too. We account for the full system, not just the algorithm.

Let's build the frontier together.

Whether you're a researcher, a hardware company, an AI team with a hard problem, or an investor who wants to back the labs working on what matters — we want to hear from you.