Estro

    Edge computing

    Edge computing. AI on your hardware.

    We bring inference systems into your infrastructure: company servers, workstations and edge devices. We design solutions that use resources efficiently and keep your data under your control.

    Let’s discuss your project

    Private hardware, efficiency and privacy

    Inference where it matters

    We deploy and integrate AI models on your hardware, close to your data and processes. We assess available CPUs, GPUs and accelerators to choose a solution suited to your project’s constraints.

    More value from your resources

    We optimize models and runtimes through quantization, model selection, and memory and workload management. We measure latency, throughput and energy use to balance output quality and operating cost.

    Your data stays in your infrastructure

    We design local inference pipelines that do not require sending data to external AI services. We configure access controls, network isolation and log retention policies around your requirements.

    From data to results, within your perimeter

    Processing runs on private hardware. Business applications receive results through local integrations, without depending on a cloud inference service.

    Client’s private infrastructure

    1. Local data

      Documents, images, sensors

    2. Optimized inference

      AI models on private hardware

    3. Operational results

      Business applications and processes

    When the project requires it, we build systems that can operate without an Internet connection, with updates managed within your infrastructure.

    What we can bring to your hardware

    Assistants and documents

    Local LLMs, enterprise document search and RAG systems to access and process confidential information.

    Computer vision

    Image and video stream analysis, OCR and quality inspection close to where data is captured.

    Sensors and signals

    Anomaly detection and analysis of industrial data or acoustic signals, including environments with limited connectivity.

    From your hardware to production

    1. Assess

      We analyze your use case, available hardware, privacy constraints and targets for quality, latency and energy use.

    2. Optimize

      We compare models and configurations on your real workloads, measuring performance, memory and energy use.

    3. Deploy

      We integrate the system with your applications and set up monitoring, maintenance and controlled updates.

    Bring inference into your infrastructure

    We start with your use case and available hardware to define an efficient solution with privacy in mind.

    Let’s discuss your project