Noise Limited builds models that predict, biology pipelines, robots that learn, IoT prototypes, AI agents
Facing a hard AI, robotics or life-science problem? Our worldwide deep-tech specialists solve it on a fixed plan.
Example briefs
Give us your brief, and we'll form the team to solve it.
The brief
We have five years of assay results. We want a model that tells us which compounds to test next.
The team we would assemble
- Machine learning engineer· lead
- Computational biologist
- Data engineer
Talent in the network
- Robot learning
- Controls
- Embedded firmware
- Computer vision
- Speech AI
- Bioinformatics
- Lab automation
- ML infrastructure
Sound familiar?
- Data & models
- Live lab data
- AI-ready systems
Your scientists rerun the same scripts and stats every week, and what they learn lives on their laptops.
AI takes over the repetitive analysis, past results become one searchable knowledge base, and models trained on it suggest what to test next.
- Data & models
- Live lab data
- AI-ready systems
Your lab still runs experiments by hand, records only the start and end points, or sends samples to outside labs.
Sensors on your own bench capture every reading in real time, straight into your own database and the ML models that learn from it. The data stays yours.
- Data & models
- Live lab data
- AI-ready systems
Are your systems, data and code ready for AI agents, or will they break something?
We audit your code and systems, connect them through secure MCP servers with the right permissions, and run agents your team approves, with every action logged.
Not sure where yours fits? Start with a two-week Discovery Sprint, from US$2,400.
Robotics too: vision and control models trained on your own robot, tested until they reach the agreed success rate.
Voice, legacy data and more: see everything we fight
How Noise Limited works
Every challenge gets its own iteration team, proposed around your problem, with a fixed plan from the brief to handover.
01About 2 minutes
Tech challenge brief
Tell us the problem in three short steps. We take the time to understand it and see whether our team can take it on, then arrange a first online meeting.
0215 minutes
Call and team proposal
A focused online call on your goal, data and constraints. We propose the iteration team for your problem, with the scope and price of the first iteration.
03From 1 week
Start the iteration
We work in Agile sprints. Each sprint has a fixed price, set by the size of the team and the scope, and agreed before it starts. Daily stand-ups in the team, and a review with you at the end of every sprint.
04Depends on scope
Build and hand over
Further iterations, each ending with something working you can test. Code, models, data and documentation are yours once paid for; keep the team on for support, or run it yourselves.
The bench
Our talent spans the deep-tech fields. We assemble a different team for each challenge, each with its own project lead.
Expertise on the bench
Project lead
Directs the team's people and agents, reviews every change and answers to you for the result.
- Hardware
- Software
- Models
- Science
- Architecture
- Code review
- Delivery
Machine learning engineer
Trains, fine-tunes and tests models, then makes them fast enough to use.
- Models
- PyTorch
- Fine-tuning
- Evaluation
Data scientist
Gets signal out of small, messy, expensive datasets and says how sure it is.
- Models
- Science
- Statistics
- Experiment design
- Forecasting
Bioinformatician
Turns sequencing and omics data into pipelines anyone can rerun.
- Software
- Science
- Nextflow
- Snakemake
- Sequencing QC
Computational biologist
Models cells and organisms so scientists can test ideas before the bench.
- Models
- Science
- Metabolic models
- Comparative genomics
Lab automation engineer
Connects models and schedulers to the instruments you already have, so experiments run overnight.
- Hardware
- Science
- Instrument integration
- Scheduling
- Instrument data
Robot learning engineer
Teaches robot arms and mobile robots new tasks from demonstrations.
- Hardware
- Models
- Imitation learning
- ROS 2
- Simulation
Perception engineer
Turns cameras, depth and sensors into something a machine can act on.
- Hardware
- Models
- Computer vision
- Depth
- Calibration
Controls engineer
Keeps motion smooth, safe and repeatable.
- Hardware
- Motion control
- Kinematics
- Safety
Embedded engineer
Writes the firmware that runs on the device and keeps working offline.
- Hardware
- Software
- C and C++
- Microcontrollers
- Edge inference
Hardware design engineer
Builds ESP32 and sensor prototypes, boards and enclosures, and turns revisions around in days.
- Hardware
- ESP32
- PCB design
- 3D printing
Agent engineer
Builds AI agents with tools, approval steps and tests before they touch real work.
- Software
- Models
- Language models
- Tool use
- Evals
Speech AI engineer
Builds voice interfaces that work in noisy rooms and in several languages.
- Models
- Speech recognition
- Text to speech
ML infrastructure engineer
Runs pipelines on GPUs reliably, with costs capped.
- Software
- Containers
- GPU queues
- Monitoring
Full-stack engineer
Builds the dashboards, apps and integrations people actually use.
- Software
- Web
- Mobile
- Cloud
AI code auditor
Reviews AI-written code for security, structure and the business logic agents miss.
- Software
- Models
- Code review
- Security
- Tests
Data engineer
Gets old databases, lab records and spreadsheets ready for models and agents.
- Software
- Science
- SQL
- Data pipelines
- Data modelling
The blueprint
We bring together specialists and know-how from around the world, and focus them on one project at a time, in flexible weekly iterations.
- Talent from everywhere
- Vetted engineers and scientists across Asia, Europe and the Americas, picked for the problem, not the postcode.
- Knowledge that compounds
- What one project learns, the next starts with: shared tools, playbooks and our own AI agents.
- Flexible Agile sprints
- Planned with you each week. Add a specialist for a sprint, pause, or scale up when the problem needs it.
Our DNA
- 2012Founded in Hong Kong
- The 2010sWeb and mobile systems for large companies
- Recent yearsMachine learning, AI agents and connected hardware
- TodayA deep-tech hub with a worldwide network
Noise Limited has been building software since 2012, starting with web and mobile systems for companies including LG U+, Samsung and Sun Hung Kai Properties. Over the last few years our work moved into machine learning, AI agents, scientific computing and connected hardware.
We are remote by design. Instead of competing with local vendors in one city, we put the world's talent and the world's best models to work on each problem, across time zones and cultures.
- Proof over promises
- We check what people can actually do, and we show working systems, not plans.
- Small, senior teams
- Project leads and the few specialists a problem needs, working with our own agents. Nobody there to pad the invoice.
- The world is the team
- Members across Asia, Europe and the Americas, picked for the problem, not the postcode.
- Good for the world
- We say no to weapons, surveillance of individuals and deception. Read our project policy.
- Write it down
- Plans, decisions and post-mortems in plain words, so you never have to guess.
Have a hard problem?
Tell us what's broken. A project lead reads it and replies, not a salesperson.
Build hard things?
Join engineers and scientists working on real problems in AI, robotics and life science. Independent contract work, paid in your currency.