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MACT.ai

Capabilities

ONE TEAM. FULL STACK.

Everything an intelligent product needs, engineered by people who talk to each other. What follows is what we actually do, in the detail an engineer would ask for.

  • 01

    AI & Models

    We select, fine-tune and deploy models that fit the product — not the other way around.

    • Model selection benchmarked against product constraints: latency, memory, power and cost.
    • Supervised fine-tuning and LoRA adapters on domain data, with evaluation harnesses.
    • Retrieval pipelines over datasheets, manuals and historical engineering knowledge.
    • Agent architectures with tool calling, guardrails and deterministic fallbacks.
    Open-source ModelsLLMVLMFine-tuningRAGComputer VisionVoice AIAI Agents
  • 02

    Hardware Engineering

    Product architecture through schematic, PCB and bring-up — designed for manufacture.

    • Compute and sensor selection with power budgets and thermal envelopes defined up front.
    • Multi-layer PCB design, DFM review, impedance control and EMC-aware layout.
    • Camera, audio and sensor integration with signal-integrity validation.
    • Bring-up, board test fixtures and design iteration through to pilot production.
    Product ArchitectureMCUMPUSoCPCBSensorsCameraConnectivityPrototype
  • 03

    Embedded Systems

    Firmware and Linux systems that stay reliable in the field, and update safely.

    • ESP-IDF, Zephyr, FreeRTOS and embedded Linux (Yocto / Buildroot) platforms.
    • Device drivers, board support packages and peripheral bring-up.
    • Provisioning, secure boot, encrypted storage and resilient A/B OTA.
    • Low-power design: duty cycling, wake sources and measured battery life.
    ESP32STM32LinuxRTOSDriversBLEWi-FiUSBOTA
  • 04

    Edge AI

    Running real models on real silicon, within the memory and milliseconds you actually have.

    • Quantization (INT8 / INT4), pruning and distillation with accuracy tracking.
    • NPU and DSP deployment across Rockchip, Amlogic, Ambarella, Jetson and Hailo.
    • Graph conversion and operator fallback strategies for constrained runtimes.
    • On-device benchmarking: latency, throughput, memory ceiling and thermal drift.
    NPU DeploymentONNXTensorRTTFLiteQuantizationModel Optimization
  • 05

    Applications

    The software people actually touch — mobile, web, desktop and on-device UI.

    • Native and cross-platform apps with BLE / Wi-Fi provisioning and live device state.
    • Web consoles and fleet dashboards for operators and support teams.
    • On-device UI with LVGL, Flutter Embedded or custom framebuffer stacks.
    • 3D and real-time visualization for sensor, spatial and robotics data.
    iOSAndroidWebDesktopDevice UI3DVisualization
  • 06

    Cloud & Connectivity

    The device cloud behind the product: telemetry, updates and the AI gateway.

    • Device identity, fleet management and staged OTA rollout with rollback.
    • MQTT and WebSocket transports built for intermittent, low-bandwidth links.
    • Telemetry pipelines, time-series storage and operational dashboards.
    • AI gateways with routing, caching, rate limiting and cost observability.
    Device CloudMQTTWebSocketOTAAPIData PlatformAI Gateway
  • 07

    Manufacturing

    The path from working prototype to units you can actually ship and certify.

    • DFM and DFA review with the manufacturing partner before design freeze.
    • EMC pre-compliance and certification planning by target region.
    • Functional test fixtures and end-of-line test procedures.
    • Pilot builds with yield tracking and failure analysis.
    DFMEMCTest FixturesPilot BuildToolingYield

HAVE AN IDEA?
LET'S BUILD IT.

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