BonsaiBONSAI
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▢ Service files/SVC-004
SVC-004

AI development

ACTIVE
Who is it for?

A good fit when a model has to run in production and on the device, not in a researcher’s notebook — reliably, on your data, and with a clear business impact.

▢ File index
  • CODESVC-004
  • STAMPACTIVE
Tags
#ml#cv#nlp#edge-inference
Key facts
Edge
On-device inference without the cloud
87%+
Accuracy in real-world conditions
MLOps
Model quality control after release
Work stages05 steps
  1. 01Stage

    Scoping

    We formalize the problem, quality metrics, and business impact.

  2. 02Stage

    Data

    Collection, cleaning, labeling, and training the labeling pipeline.

  3. 03Stage

    Model

    Baseline model, iterations, experiments, architecture comparison.

  4. 04Stage

    Deployment

    Optimization for target hardware (ONNX, TFLite, TensorRT), integration.

  5. 05Stage

    MLOps

    Model quality monitoring in production, retraining, A/B tests.

What you get
  • ✓01Trained models and a reproducible training pipeline
  • ✓02Inference service (REST / gRPC / edge runtime)
  • ✓03Labeling and data quality control tools
  • ✓04Dashboard of model quality metrics in production
Why BonsaiWhy engineering teams work with us
01

Edge-first

Models run on the device, not just on a GPU server.

02

Data for the task

We build labeling and training even on small and proprietary datasets.

03

Engineering, not demos

We take models to stable 24/7 operation in production.

04

MLOps

Quality monitoring, retraining, and A/B tests in production.

↘ Case studies
Anomaly detection system
Anomaly detection systemMultimodal model for aircraft fault analysis
Yandex
YandexResearch on language model sensitivity to writing style
Federated learning
Federated learningResearch on distributed training methods for ML models
Eye-tracking system
Eye-tracking systemDevice control through gaze tracking
Service pricingPrice list

Prices shown are starting prices and depend on scope — the final estimate follows an audit of your task. Choose an engagement model:

Fixed price

Custom development
  • —Price and timeline are fixed and do not change
  • —Weekly reporting and full transparency
  • —Warranty on the work and full confidentiality
  • —Turnkey result with 24/7 support
from $18K
Per AI module

Time & Materials

Phased development
  • —The project is split into stages (sprints)
  • —Requirements and budget can change
  • —A dedicated team for your project
  • —A flexible model for complex projects
from $3.5K
Per 1-week sprint
Staff augmentation — dedicated IT specialists
Hourly rates and ready-made teams — one price list for all areas
View rates →
↘ Related solutions
AI & data analytics→
↘ Expertise
↘ Technologies
Other files in the catalog11 FILES

Assess your AI use case

We’ll run a technical review:

  • —validate target metrics
  • —check data sufficiency
  • —pick a model and hardware
  • —provide an estimate and timeline
Discuss your project→Book an ML audit→