Defined Scope
Each contribution is documented with goals, responsibilities, acceptance criteria, delivery, and dependencies.
R&D AND TECHNOLOGY COLLABORATIONS
We unite different areas of expertise around one goal;
we transform research into applicable technology.
10noo's own software and product development team manages artificial intelligence, embedded systems, hardware, cloud, data, security, and product experience in a common architecture. Depending on the need, technoparks, technology centers, universities, laboratories, specialized R&D companies, and production partners provide complementary competencies to the project.
10NOO CORE TEAMSINGLE PRODUCT ARCHITECTUREEXPERT COLLABORATIONMEASURABLE VERIFICATION
10NOO R&D COLLABORATION FABRIC · ACTIVECORE TEAM → SPECIALISTS → VALIDATED PRODUCT
PARTNERS DO NOT REPLACE THE CORE TEAM · THEY ADD EXPERTISE, TESTING AND SCALING TO THE PROJECTOWNERSHIP · CONTROL · COLLABORATION
01 / WORKING MODEL
Product ownership remains central;
expertise is linked to the project in a controlled manner.
10noo manages the product objective, system architecture, software development, integration and delivery responsibility with its own core team. External experts only contribute within the defined task, data, output and intellectual property limits.
01 · CORE OWNERSHIP10noo Core TeamProduct goal · architecture · code · integration · security · delivery
02 · PROJECT CELLSInterdisciplinary Project TeamAI · software · embedded · hardware · UX · QA · operations
03 · EXTENDED R&D NETWORKComplementary Expertise NetworkTechnopark/technology center · university · laboratory · specialist company · manufacturer
Minimal Permission
The partner only accesses the data, systems, and development environment necessary for their task.
Intellectual Property and Release
Code, model, dataset, design, documentation, license, and third-party components are tracked.
Single Validation Standard
Every output, internal or external, undergoes the same testing, safety, and acceptance process.
02 / FROM IDEA TO COMMERCIAL PRODUCT
Research does not stop at a presentation;
a measurable product journey
Each stage generates proof that reduces the cost and risk of the next stage. Ideas whose feasibility has not been validated are not directly taken to large-scale development or production.
TEST FAILUREThe assumption, architecture, or prototype returns to the relevant stage; the issue is not carried over to the next step.REVALIDATE
03 / INTERACTING DISCIPLINES
Not isolated strengths, but
one integrated system in which every discipline complements the others.
Product integrity is protected by shared decision records, versioned interfaces, and explicit acceptance criteria. Hardware changes affect firmware; model changes affect Edge performance; user experience decisions affect API and operation together.
Artificial Intelligence and Data
Model strategy, data preparation, RAG, vision, evaluation, MLOps, and secure deployment.
Web, Mobile, Cloud, and API
Applications, enterprise services, integrations, data flows, and operation dashboards.
Embedded Software and IoT
Firmware, device ID, protocol, OTA, telemetry, Edge AI, and device management.
Electronics and Hardware
PCB, sensor, processor, power, connectivity, prototyping, test fixture, and production readiness.
Security and Compliance
Threat model, access, encryption, secure updates, data policy, and legislation.
Product and User Experience
User needs, workflow, interface, field feedback, support, and lifecycle.
Testing and Datafication
Function, performance, integration, security, environmental, field, and acceptance testing.
Manufacturing and Scaling
DFM/DFT, procurement, certification, manufacturing testing, release management, and quality tracking.
04 / EXPERIMENT, EVIDENCE AND DECISION
The output of every stage
is evidence for the next investment decision.
We do not measure R&D success solely by the phrase "it worked". The purpose of the experiment, hypothesis, data set, conditions, acceptance threshold, reason for failure and reproducible result are recorded.
- Hypothesis and success/failure criterion
- Representative data and field conditions
- Control group, comparison and reference solution
- Performance, safety, cost and user impact
- Error logging, root cause and remediation verification
- Go / Revise / Stop decision gates
EVIDENCE-DRIVEN R&DHYPOTHESIS → TEST → DECISION
FAILED EXPERIMENT IS NOT A LOSS · IT IS A RECORD THAT STRENGTHENS THE NEXT DECISIONREPEATABLE · TRACEABLE
05 / TYPES OF TECHNOLOGY COLLABORATION
We connect each need with the right expertise;
we protect product integrity from one center.
Collaboration is not a claim to an address or signboard. It is a project relationship that meets a specific research, testing, expertise, laboratory, prototyping, manufacturing, or scaling need.
University and Academic Expertise
Scientific method, field expertise, literature, research design, and academic consultancy as needed.
Laboratory and Testing Infrastructure
Electronic, environmental, RF, EMC, safety, performance, material, or specialized device testing.
Technopark and Technocity Network
Project-based technology collaborations with software developers and R&D companies without claiming a campus.
Expert R&D Companies
Adding specific model, protocol, hardware, security, industry or certification expertise to the project.
Manufacturer and Engineering Partners
Prototype, DFM/DFT, mold, PCB, test fixture, pilot production and mass production preparation.
Platform and Technology Providers
Processor, GPU/NPU, cloud, model, database, security, connectivity and development tools.
06 / PROJECT MANAGEMENT AND TRUST
Move fast without losing control.
A common development discipline.
Decisions, interfaces, and experiment results are not tied to individuals. Release, responsibility, acceptance criteria, security, and change impact are tracked throughout the project.
Single Product Plan
Internal team and partners work on the same goal, dependency, and priority plan.
Decision Log
The reason for selection, which alternative was eliminated, who approved, and what the impact was are recorded.
Release and Traceability
Code, model, data, hardware revision, documentation, and test results are linked.
Privacy and Access
Project space, data, repository, device, and document access are restricted by role and scope.
Cross-Technical Review
Critical output is reviewed by an expert outside the manufacturer in terms of architecture, testing, and security.
Information Era
Source code, architecture, installation, testing, maintenance, and operation information are delivery criteria.
10NOO DIGITAL · RESEARCH TO PRODUCT