SOLUTIONS

Solutions & Capabilities

Solving real problems with engineering methods. Here are the solutions we deliver most often.

  • Computer Systems Integration
  • Machine Learning & AI Application Engineering
  • Integrated Circuits & Smart Consumer Electronics

SOLUTION 01 · VIRTUALIZATION & HCI

Virtualization and HCI: architecture chosen to fit your scale and operations capability.

No single architecture fits every case. Based on your workloads, pace of growth, existing investments and the capabilities of your operations team, we choose the right combination of traditional three-tier, hyper-converged and distributed storage architectures, and plan the migration path.

Typical Scenarios

Legacy server consolidationBranch offices and edge server roomsR&D and test environmentsData and AI training storageStorage and data protection upgrades

Solution Architecture

Traditional three-tier

Separate servers, storage network and storage arrays. Mature and stable, it makes the most of existing investments.

Best for: existing storage investments, stable workloads

Hyper-converged (HCI)

Compute and storage converged on standard nodes: fast to deploy, scales node by node, managed as one.

Best for: fast go-live, node-by-node expansion

Distributed storage

Scales out capacity and performance, suited to massive unstructured data and AI training data.

Best for: massive unstructured data and AI data

Delivery Method

  1. Current-state inventory and workload sizing
  2. Architecture selection and capacity planning
  3. Pilot validation
  4. Phased migration
  5. Acceptance, documentation and operations handover
  • Higher resource utilization
  • Faster go-live
  • Simpler operations
  • Smoother scaling

SOLUTION 02 · AI ENGINEERING

AI engineering delivery: from scenario definition to continuous iteration.

The most common risks in AI projects lie not in the algorithms themselves, but in unclear scenario definitions, data that doesn't reflect the field, and no one maintaining the system after deployment. We manage these risks with a consistent engineering process.

Typical Scenarios

Smart cleaning and mobile robotsUrban managementTraffic managementWorkplace safetyIndustrial quality inspection

Delivery Method

  1. Scenario definition

    Clarify business goals, operating environment and acceptance criteria, and assess whether AI is the right solution.

    Output: scenario description and acceptance criteria

  2. Data collection and labeling

    Collect samples for the target scenario, build a labeling taxonomy, and use semi-automated labeling to improve efficiency.

    Output: datasets and labeling taxonomy

  3. Model training and evaluation

    Model selection, training and multiple rounds of evaluation, validated on real-world samples.

    Output: evaluation report

  4. Engineering integration and deployment

    Model slimming and inference acceleration, deployed to edge devices, vehicles or servers and integrated with business systems.

    Output: deployable models and APIs

  5. Operations and iteration

    Continuously monitor performance after launch, collect hard cases, and iterate the model regularly.

    Output: monitoring and iteration plan

SOLUTION 02a · AUTONOMOUS SWEEPER

Autonomous sweepers with adaptive obstacle avoidance: see clearly, judge accurately, move steadily.

On campus and factory roads, pedestrians, vehicles and temporary obstacles can appear at any time. A sweeper must handle these changes safely while completing its coverage work. The diagram below shows a typical on-vehicle system architecture for this type of sweeper.

Solution Architecture

INPUTEnvironmental sensors (cameras, etc., configured per vehicle model)

INPUTLocalization and odometry

  1. Perception

    Detects pedestrians, vehicles, curbs and drivable areas

  2. Obstacle classification

    Static / dynamic

  3. Decision

    Go around / slow down / wait

  4. Planning

    Global coverage + local trajectory

  5. Control

    Tracking control and on-vehicle execution

CLOUDCloud dispatch and monitoring

Overhead view of a city intersection with vehicles and pedestrians crossing
City intersection from above: a multi-object perception and trajectory scenario
Perception

Vision algorithms detect pedestrians, vehicles, curbs, drivable areas and all kinds of obstacles.

Decision

Distinguishes static from dynamic obstacles and adaptively chooses to go around, slow down or wait.

Planning

Combines global coverage paths with local avoidance trajectories for smooth, executable motion.

Deployment

On-vehicle inference deployment, dispatch and monitoring application development, on-site testing and parameter tuning.

Solution details vary by scenario. Feel free to email us about your specific needs.

SOLUTION 02b · VISUAL RECOGNITION

Visual recognition scenarios, combined and customized to your needs.

Vision capabilities can be combined by event type, deployed to edge devices or servers, and extended with new recognition categories as your business grows.

Typical Scenarios (Visual Recognition)

Urban management

Detecting events such as street-environment issues, road encroachment and overflowing bins.

Traffic management

Detecting illegal parking, riders without helmets and faulty traffic facilities.

Workplace safety

PPE compliance, unsafe behavior, and smoke and fire alerts.

Low-altitude inspection

Counting people and vehicles in drone video.

Industrial quality inspection

Visual inspection for part integrity, missing or damaged markings and more.

Custom scenarios

Data and algorithms customized for special requirements.

SOLUTION 03 · IC & DEVICES

Chips and smart devices: integrated selection and supply chain services.

The success of a hardware product is often decided at the component selection and volume supply stages. We handle selection, solution development and supply chain within one team, reducing back-and-forth between design and supply.

Typical Scenarios

Component selection for new productsSmart device solution developmentVolume inventory and delivery coordination

Solution Architecture

Components

Selection recommendations for chips and related electronic components, based on a product's performance, power and cost requirements.

Product solutions

Taking part in product definition and solution development for smart consumer electronics such as smart cameras and fitness bands.

Supply

Inventory planning and delivery coordination to keep products in stable supply across different markets.

Delivery Method

  1. 01

    Requirements and specifications

    Define performance, power, cost and size requirements.

  2. 02

    Selection

    Compare candidate components and designs, and recommend a selection.

  3. 03

    Solution development

    Take part in product definition and solution development.

  4. 04

    Supply and delivery

    Inventory planning and delivery coordination.

NEXT About Us Learn about how we work, our values and our three core services.

Want to discuss a specific solution?

Whether it's architecture selection, delivering an AI project, or component selection and supply, email us with your requirements.

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