Seamless Enterprise Deployment

Seamless Enterprise Deployment

Flexible by design. Scalable by default. Fully under your control.

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Deployment Options

Deployment Options

Deployment Options

Our architecture supports cloud, on-premises, and (soon) edge deployment — giving you full flexibility based on your infrastructure, compliance, and control requirements.

Cloud-Based

Deploy and scale effortlessly on secure, managed infrastructure — optimized for speed, efficiency, and accessibility.

Cloud-Based

Deploy and scale effortlessly on secure, managed infrastructure — optimized for speed, efficiency, and accessibility.

Cloud-Based

Deploy and scale effortlessly on secure, managed infrastructure — optimized for speed, efficiency, and accessibility.

On-Premises

Operate solely within your environment, ensuring complete control over data, models, and infrastructure.

On-Premises

Operate solely within your environment, ensuring complete control over data, models, and infrastructure.

On-Premises

Operate solely within your environment, ensuring complete control over data, models, and infrastructure.

Edge-Device (coming soon)

Bring intelligence directly to edge devices for real-time inference without relying on cloud connectivity.

Edge-Device (coming soon)

Bring intelligence directly to edge devices for real-time inference without relying on cloud connectivity.

Edge-Device (coming soon)

Bring intelligence directly to edge devices for real-time inference without relying on cloud connectivity.

Plug-in

Plug-in

Plug-in

Plug in your data and systems — fast and frictionless

Plug in your data and systems — fast and frictionless

Implementation

  1. Define requirements and constraints

  2. Describe API and UI / UX

  3. Train the model

Integration

  1. Connect the model to the data sources

  2. Connect the model with the UI

  3. Set RAG and any other rules/logic constraints

Training Process

(after the use case is approved)

1

Identify and acquire the right dataset for the use case

1

Identify and acquire the right dataset for the use case

1

Identify and acquire the right dataset for the use case

2

Data discovery & preprocessing (as needed)

2

Data discovery & preprocessing (as needed)

2

Data discovery & preprocessing (as needed)

3

Infrastructure setup

3

Infrastructure setup

3

Infrastructure setup

4

Training baseline models

4

Training baseline models

4

Training baseline models

5

Baseline model testing

5

Baseline model testing

5

Baseline model testing

6

Capture performance metrics

6

Capture performance metrics

6

Capture performance metrics

7

Optimization to generate the next version of models

7

Optimization to generate the next version of models

7

Optimization to generate the next version of models

8

Benchmarking

8

Benchmarking

8

Benchmarking

9

Final models

9

Final models

9

Final models

10

Evaluation, user training, documentation, and delivery

10

Evaluation, user training, documentation, and delivery

10

Evaluation, user training, documentation, and delivery

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Copyright © 2025. Symbolic Mind®. All rights reserved

Copyright © 2025. Symbolic Mind®. All rights reserved