From trained model to production fleet.
In hours, not months.
AgyleSoft builds productized edge AI deployment systems for industrial, logistics, and regulated environments. We automate model conversion, fleet rollout, monitoring, and version governance across Azure IoT Hub, Microsoft AI infrastructure, and NVIDIA Jetson devices.
From live sensor input to edge decisioning in one continuous loop
NVIDIA Jetson at the edge, Azure IoT Hub for fleet control
Local inference, secure device orchestration, and observability in one operational loop.
We help enterprises move from AI experiments to fleet-scale deployment
The real challenge is not model training. It is turning a qualified model into a reliable, governed, factory-ready deployment that works across real devices and operational constraints.
Typical client needs
- Deploy AI models across a device fleet without manual device-by-device rollout
- Reduce time from model readiness to field deployment
- Track model versions, device state, and operational performance
- Support auditability and controlled rollout in regulated environments
- Run edge AI across pharma, logistics, drone, or industrial operations
We are not for
- Purely generic AI consulting without deployment execution
- Companies seeking only slide-level strategy with no field deployment roadmap
- Non-operational experimentation without real fleet or production use cases
- Projects that need a one-off PoC but no operational rollout model
AI deployment at the edge,
built for real operations.
AgyleSoft Edge AI Runtime connects cloud intelligence with device-level execution and fleet visibility.
Operational AI services designed for real-world fleets.
From model conversion to fleet governance, each capability is built to work on live devices and production environments.
Model Conversion & Optimization
We automate the critical path from PyTorch/TensorFlow models to optimized edge-ready formats for NVIDIA and other target hardware, reducing the time and risk of manual conversion.
02Fleet Rollout via Azure IoT Hub
Device twins, desired-state control, and telemetry make fleet deployment repeatable, traceable, and resilient, even across distributed environments.
03Operational Monitoring
We surface device health, model version compliance, inference performance, and rollback readiness in one operational view.
04Microsoft Solutions
AgyleSoft continues to support enterprise modernization initiatives across Azure, Microsoft 365, modern workplace, AVD, and security-led transformations.
A Structured Framework for Complex Transformation
Here’s what working with us actually looks like — from first call to running in production.
Built for model rollout across real-world fleets
Model rollout from lab to live production lines in hours — not manual field-by-field deployment cycles.
A manufacturing operation needed to deploy a vision model across inspection points without repeating the same conversion, validation, and update process on every device. The challenge was not the model itself — it was getting the model to scale reliably across live operations.
AgyleSoft Edge AI Runtime standardizes the path from model registry to device fleet deployment, enabling controlled rollout, operational visibility, and version auditability across the environment. The output is a faster, safer, repeatable deployment model that supports regulated operations.
Deployment model: per device, with batch and fleet-aware rollout governance and operational monitoring built in.
What the product enables
Ready to evaluate a pilot?
Book a pilot →We needed a repeatable way to deploy and monitor AI across a multi-device environment. The platform removed the biggest source of operational drag: model rollout across the field.
What stood out was not just deployment automation, but the level of governance around model versioning and fleet readiness. That matters when the deployment is operational, not experimental.
Built for edge deployment in operations that matter
We focus on deployment-heavy AI workloads where consistency, traceability, and field-scale rollout create measurable business value.
Drone Fleet AI
Model deployment across autonomous and assisted fleet operations with version governance, field control, and low-friction rollout for remote device groups.
- Fleet-wide model updates
- Operational consistency
- Field rollout control
Pharma Inspection Line
AI-driven quality inspection and compliance-aware deployment for regulated environments where model traceability and version control are business-critical.
- Version audit trail
- Inspection automation
- Regulated operation support
Last-Mile Logistics
Vision-based detection, quality checks, and operational intelligence for package movement, dock operations, and warehouse throughput optimization.
- Warehouse AI deployment
- Fleet consistency
- Operational efficiency
Industrial Quality Control
Deployment of vision and inference models across production lines where consistency and uptime matter more than experimentation alone.
- Edge performance tuning
- Device fleet governance
- Operational rollout
Business-led Microsoft transformation with practical execution
AgyleSoft supports enterprise modernization across Azure, Microsoft 365, identity, endpoint management, and secure workplace transformation — kept concise and focused on business outcomes.
Azure Modernization
Landing zones, cloud architecture, migration planning, governance, and modernization roadmaps built for business continuity.
Modern Workspace
Microsoft 365 productivity, collaboration, governance, and adoption design for distributed and hybrid teams.
Azure Virtual Desktop
Secure VDI and endpoint strategy that improve user experience, operational control, and cost efficiency.
Identity & Security
Entra ID, Conditional Access, security baselines, and role-based access that support resilient digital operations.
Start the conversation
Tell us what you’re working on. We’ll review it before we respond — so our first reply is actually useful, not a generic “thanks for reaching out.”
Ready to pilot?
Deploy AI to the edge with a product-first rollout model.
We help teams evaluate an edge AI deployment path, define the right fleet model, and scope a pilot around real operational outcomes. The focus is on deployment readiness, model governance, and business impact — not slideware.
Book a pilot discussion →We respond within 1 business day. Hyderabad, India · AI deployment across industrial and operational environments.