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Build and Deploy Smarter with
Cyfuture AI's Serverless Inferencing

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Lightning-Fast Auto-Scaling

Cyfuture AI serverless inferencing automatically scales GPU resources from zero to thousands of instances in milliseconds, ensuring optimal performance without manual intervention or resource waste.

Next-Level GPU Architecture

Cost-Optimized Pay-Per-Use Model

Our serverless inference GPU platform eliminates idle costs by charging only for actual compute time, delivering up to 70% cost savings compared to traditional dedicated GPU deployments.

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Seamless Multi-Framework Support

Deploy any AI model instantly with native support for TensorFlow, PyTorch, ONNX, and custom frameworks through our unified serverless inference API, reducing deployment complexity from weeks to minutes.

Deploy your AI models instantly- Your no servers, no limits.

Try Cyfuture AI's Serverless Inferencing today!

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The Infrastructure-Free AI Revolution:
Serverless Inferencing Redefined

Serverless inference represents the ultimate abstraction in AI deployment, where machine learning models execute predictions without any server management overhead. This revolutionary approach allows developers to deploy trained models that automatically scale from zero to thousands of requests per second, with cloud providers handling all infrastructure complexities behind the scenes.

The game-changing significance of serverless inferencing lies in its ability to democratize AI deployment across organizations of all sizes. By eliminating capacity planning, server configuration, and resource management, development teams can focus purely on model optimization while achieving 70% faster time-to-market. For GPU-intensive workloads, serverless inference GPU solutions provide on-demand access to high-performance computing resources, making advanced AI capabilities accessible through a simple pay-per-use model that transforms both cost structure and operational complexity.

How Serverless Inferencing Works:
Architecture and Workflow?

Serverless inferencing in Cyfuture AI eliminates the need for server management by automatically provisioning compute resources only when requests arrive.

An API call triggers the platform-part of our AI Lab as a Service-which instantly selects the best CPU or GPU instances, loads the model from warm containers with pre-loaded frameworks, and delivers results with sub-second latency.

Once processing is done, resources are freed immediately, ensuring pay-per-use cost efficiency. Powered by intelligent load balancing and auto-scaling, it can handle workloads from a single request to thousands in parallel. The system also optimizes CPU/GPU allocation for diverse AI applications like computer vision and natural language processing, ensuring high performance and scalability

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Work Flow

Model Upload

Pre-trained model is uploaded via dashboard or CLI.

API Call Trigger

Inference request sent via REST or gRPC API.

Auto Resource Allocation

Platform selects optimal CPU/GPU resources instantly.

Model Loading

Model and dependencies loaded into warm containers (minimal cold start).

Inference Execution

Input processed by the model with load balancing and auto-scaling.

Result Delivery

Low-latency output sent back to the requester.

Resource Release

Compute resources freed immediately; pay only for usage.

Monitoring

Real-time logs and performance insights available on the dashboard.

Voices of Innovation: How We're Shaping AI Together

We're not just delivering AI infrastructure-we're your trusted AI solutions provider, empowering enterprises to lead the AI revolution and build the future with breakthrough generative AI models.

KPMG optimized workflows, automating tasks and boosting efficiency across teams.

H&R Block unlocked organizational knowledge, empowering faster, more accurate client responses.

TomTom AI has introduced an AI assistant for in-car digital cockpits while simplifying its mapmaking with AI.

Affordable Serverless Inferencing from $0.09 per Million Tokens

The starting price for Cyfuture AI's Serverless Inferencing is approximately $0.09 per 1 million tokens for text models with up to 4 billion parameters. This affordable, pay-per-use pricing allows scalable AI deployments without upfront infrastructure costs.

Dollar INR

Up to 4B

Base Model

$0.085

/1M Tokens | input and output

4.1B - 8B

Base Model

$0.17

/1M Tokens | input and output

8.1B - 21B

Base Model

$0.255

/1M Tokens | input and output

21.1B - 41B

(e.g. Mistral 8x7B)

$0.68

/1M Tokens | input and output

41.1B - 80B

Base Model

$0.765

/1M Tokens | input and output

80.1B - 110B

Base Model

$1.44

/1M Tokens | input and output

MoE 1B - 56B

(e.g. Mistral 8x7B)

$0.425

/1M Tokens | input and output

MoE 56.1B - 176B

(e.g. DBRX, Mistral 8x22B)

$0.96

/1M Tokens | input and output

Deepseek-v3

Base Model

$0.72

/1M Tokens | input and output

Deepseek-r1

Base Model

$6.40

/1M Tokens | input and output

DeepSeek LLM Chat 67B

Base Model

$0.765

/1M Tokens | input and output

Yi Large

Base Model

$2.55

/1M Tokens | input and output

LLAMA 3 70B

Base Model

$0.88

/1M Tokens / input and output

Meta Llama 3.1 405B

Base Model

$2.55

/1M Tokens / input and output

Mistral 7B

Base Model

$0.25

/1M Tokens | input and output

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Note: The prices listed are calculated per 1 million tokens, encompassing both input and output tokens for various models, including chat, multimodal, language, and code models. This pricing structure allows users to estimate costs based on their usage of the models in different applications.

Key Benefits of Serverless Inferencing for Enterprises

Unmatched Performance
Zero Infrastructure Management

Cyfuture AI's serverless inferencing eliminates the complexity of GPU provisioning, scaling, and maintenance. Enterprises can deploy AI models instantly without managing underlying infrastructure, allowing development teams to focus on innovation rather than operational overhead.

Unmatched Performance
Cost-Efficient Pay-Per-Use Model

With serverless inference, organizations pay only for actual compute time used during model execution. This granular pricing model can reduce AI inference costs by 40-70% compared to traditional always-on GPU instances, making advanced AI accessible to businesses of all sizes.

Unmatched Performance
Instant Auto-Scaling Capabilities

Serverless inference GPU resources automatically scale from zero to thousands of concurrent requests in milliseconds. This elastic scaling ensures optimal performance during traffic spikes while eliminating costs during idle periods, perfect for unpredictable AI workloads.

Effortless Scalability
Accelerated Time-to-Market

Deploy production-ready AI models in minutes rather than weeks. Cyfuture AI's serverless inferencing platform handles load balancing, fault tolerance, and version management automatically, enabling enterprises to launch AI-powered features 5x faster than traditional deployment methods.

Enterprise-Grade Security
Enterprise-Grade Reliability

Built-in redundancy and multi-zone deployment ensure 99.9% uptime for critical AI applications. The serverless inference architecture automatically handles failovers and traffic distribution, providing enterprise-level reliability without additional configuration complexity.

Security and Reliability in Serverless Inferencing

Cyfuture AI's serverless inferencing platform delivers enterprise-grade security through multi-layered protection, end-to-end encryption, and compliance with SOC 2 and ISO 27001 standards. Our secure model isolation ensures that sensitive data and AI models remain protected throughout the inference pipeline while maintaining the flexibility of serverless computing.

Our serverless inference GPU infrastructure guarantees 99.9% uptime through built-in redundancy, automatic failover, and distributed computing across multiple availability zones. Combined with real-time monitoring and intelligent load balancing, organizations can deploy serverless inference workloads with confidence, knowing their AI applications will perform reliably even during peak demand periods.

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Build & Scale: Serverless AI Deployment with Cyfuture AI

Launching your serverless AI deployment has never been more streamlined. Cyfuture AI's serverless inferencing platform eliminates the complexity of infrastructure management, allowing you to deploy machine learning models with zero server provisioning or scaling concerns. Simply upload your trained models, configure your endpoints, and let our platform handle the automatic scaling, load balancing, and resource optimization-ensuring your AI applications respond instantly to demand fluctuations while maintaining cost efficiency.

Our serverless inference architecture is designed for production-grade AI workloads, featuring sub-second cold start times and intelligent resource allocation across our global serverless inference GPU network. Whether you're deploying RAG-based AI systems, computer vision models, natural language processing applications, or complex deep learning algorithms, Cyfuture AI's platform automatically provisions the optimal GPU resources for each inference request, scaling from zero to thousands of concurrent predictions seamlessly.

Experience the future of AI deployment where operational overhead becomes obsolete. With built-in monitoring, automatic failover, an extensive AI model library, and pay-per-inference pricing, you can focus entirely on model performance and business logic while Cyfuture AI manages the underlying infrastructure complexity. Start your serverless AI journey today and transform how your organization delivers intelligent applications at scale.

Why Cyfuture AI Stands Out

True Serverless
Architecture

Cyfuture AI's serverless inferencing platform eliminates infrastructure management complexity, automatically scaling GPU resources from zero to peak demand in milliseconds without manual intervention.

Cost-Efficient Pay-Per-
Use Model

Pay only for actual inference and fine-tuning compute time with our serverless inference pricing model, reducing costs by up to 70% compared to traditional always-on GPU instances.

High-Performance
GPU Optimization

Purpose-built serverless inference GPU infrastructure delivers sub-100ms response times with automatic load balancing across distributed GPU clusters for maximum throughput.

Enterprise-Grade
Reliability

Built-in fault tolerance and multi-zone redundancy ensure 99.9% uptime for mission-critical serverless inferencing workloads with automatic failover capabilities.

Developer-First
Experience

Deploy AI models instantly with simple API calls and pre-built integrations, enabling developers to focus on innovation rather than infrastructure complexity in serverless inference environments.

Seamless Security
& Compliance

Cyfuture AI ensures enterprise-grade data protection with end-to-end encryption, role-based access controls, and compliance with global standards like GDPR, HIPAA, and SOC 2, making serverless inferencing both secure and trustworthy.

Trusted by the best names in AI

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FAQs: Serverless Inferencing

Serverless inferencing is a cloud-based approach to deploying machine learning (ML) models where the infrastructure is fully managed by the cloud provider. You don't need to provision or manage servers; instead, you deploy your model, and the provider automatically scales the compute resources needed to serve inferences..

  • Cost-efficiency: Pay-per-use model saves money during idle times.
  • Scalability: Automatically handles large volumes of inference requests.
  • Ease of deployment: No need to manage infrastructure.
  • Faster time-to-market: Simplifies the MLOps pipeline.
  • Real-time predictions in web or mobile apps (e.g., recommendations, personalization).
  • NLP tasks like sentiment analysis or text classification.
  • Image classification in IoT or edge-connected devices.
  • Any ML inference workload with unpredictable traffic patterns.

Yes, serverless inferencing can serve real-time predictions, but latency may vary depending on the provider and whether cold starts occur. Some providers offer optimizations to reduce startup delays.

Serverless inferencing can support a wide range of models, including natural language processing (NLP), computer vision, speech recognition, and recommendation systems, as long as they meet the provider's runtime and resource limits.

You can expose models as REST or gRPC APIs, and SDKs are available for multiple languages. Cyfuture AI also integrates seamlessly with MLOps pipelines, CI/CD tools, and provides real-time dashboards for monitoring.

Typical applications include fraud detection, real-time recommendation systems, chatbots, image analysis, and large language model deployments where responsiveness and elastic scaling are critical.

Train your model using a supported framework, upload the model via the Cyfuture AI dashboard or CLI, configure inference parameters, and deploy. You're then ready to make predictions through secure endpoints with monitoring and logging enabled by default.

Deploy Models in Seconds

Instantly deploy and scale AI models without managing servers - pay only for what you use.

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