What cloud platforms do you deploy AI agents on?

We deploy on AWS, Google Cloud, Azure, and on-premise infrastructure. We also support hybrid and multi-cloud setups for redundancy and compliance requirements.

How do you handle scaling during traffic spikes?

We configure auto-scaling policies based on queue depth, request latency, and GPU utilization. Agents scale up within seconds and scale down to zero when idle to optimize costs.

Can you deploy agents that use different LLM providers?

Yes. Our deployment infrastructure is model-agnostic — we support OpenAI, Anthropic, Google, open-source models via vLLM/TGI, and custom fine-tuned models all within the same environment.

How do you handle model updates without downtime?

We use blue-green and canary deployment strategies. New model versions are validated in staging, deployed alongside the current version, and traffic is gradually shifted with automatic rollback on error spikes.

What monitoring and alerting do you set up?

We instrument every agent with structured logging, distributed tracing, token usage metrics, latency percentiles, and error tracking — with alerts routed to Slack, PagerDuty, or your preferred incident management tool.

Do you support on-premise or air-gapped deployments?

Yes. For organizations with strict data residency or compliance requirements, we deploy agents entirely on-premise with self-hosted model serving and no external API dependencies.

How do you optimize inference costs?

We use a combination of model quantization, request batching, response caching, spot/preemptible GPU instances, and right-sizing compute to reduce costs by 40-60% compared to naive deployments.

Can you manage a fleet of different AI agents?

Yes. We orchestrate multi-agent fleets with service discovery, message routing, shared state management, and centralized observability — treating your agent ecosystem as a managed platform.

AI Agent Deployment

Deploy AI agents that scale from prototype to production.

We handle the infrastructure, orchestration, and operations so your AI agents run reliably at scale — with automated scaling, real-time monitoring, secure environments, and zero-downtime deployments.

OUR PROCESS

Infrastructure Assessment

We evaluate your current infrastructure, cloud environment, and workload requirements to design the optimal deployment architecture for your AI agents.

Environment & Pipeline Setup

We provision containerized runtimes, configure CI/CD pipelines, and establish staging and production environments with infrastructure-as-code.

Agent Containerization & Packaging

We package your AI agents into production-ready containers with dependency management, model weight optimization, and runtime configuration.

Deployment & Scaling Configuration

We deploy agents with auto-scaling policies, load balancing, health checks, and failover strategies to handle variable traffic and demand spikes.

Observability & Monitoring

We instrument agents with structured logging, distributed tracing, performance metrics, and alerting for full visibility into agent behavior and health.

Optimization & Ongoing Operations

We continuously optimize inference costs, latency, and throughput — managing model updates, A/B rollouts, and capacity planning as your usage grows.

Why choose us

Production-grade reliability

99.9% uptime SLAs with automated failover, health checks, and self-healing infrastructure designed for mission-critical agent workloads.

Cost-optimized scaling

Right-sized compute, GPU scheduling, and spot instance strategies that reduce inference costs by up to 60% without sacrificing performance.

Cloud-agnostic deployment

Deploy across AWS, GCP, Azure, or on-premise — we build portable infrastructure that avoids vendor lock-in and meets your compliance requirements.

Zero-downtime updates

Blue-green and canary deployment strategies ensure agent updates roll out smoothly without interrupting active sessions or losing context.

Security & isolation

Network segmentation, secrets management, encrypted model storage, and role-based access controls for every deployed agent environment.

Ready to deploy your AI agents at scale?

Talk to our deployment engineers about your infrastructure needs, scaling requirements, and rollout strategy.

OUR AI EXPERTISE

At Storygame, we bring deep technology experience together with a strategic vision to help companies deploy AI solutions that solve real business problems.

Containerized Agent Runtimes

Package and deploy AI agents in Docker/Kubernetes with optimized base images, GPU scheduling, and resource limits for predictable performance.

Auto-Scaling & Load Balancing

Dynamic scaling policies that spin up agent replicas based on queue depth, latency targets, and traffic patterns — scaling down to zero when idle.

CI/CD for AI Agents

Automated pipelines for testing, building, and deploying agent updates with model versioning, rollback capability, and staged rollouts.

Real-Time Observability

Full-stack monitoring with agent-level metrics, token usage tracking, latency percentiles, error rates, and custom dashboards for operational visibility.

Edge & Hybrid Deployment

Deploy lightweight agents at the edge for low-latency use cases, with hybrid architectures that route between edge and cloud based on complexity.

Model Serving & Optimization

Serve models with TensorRT, vLLM, or TGI for maximum inference throughput — with quantization, batching, and caching strategies.

Multi-Agent Deployment Orchestration

Deploy and manage fleets of cooperating agents with service mesh, message queues, and shared state management for complex multi-agent systems.

GENERATIVE AI & LLM SOLUTIONS

Our Generative AI & LLM Solutions utilise the latest in artificial intelligence and large language models, building intelligent platforms. We develop unique AI agents and automation tools to create content, understand data and optimize workflows.

We specialise in creating Generative AI and LLM solutions that enable efficiency and innovation. At our AI agency, we create bespoke AI agents, intelligent chatbots and LLM-integrated platforms that fit your business challenges and data ecosystem.

OUR AI & LLM SERVICES

We deliver secure, scalable Generative AI solutions – from intelligent agent development and LLM integration to AI-powered automation and strategic consulting.

Services

Kubernetes Agent Deployment
GPU Infrastructure Management
CI/CD Pipeline for AI Agents
Auto-Scaling & Load Balancing
Observability & Monitoring
Model Serving & Optimization
Edge Deployment
Multi-Agent Fleet Management

Enterprise AI Agent Deployment

Deploy and operate production AI agent infrastructure — from single-agent services to complex multi-agent fleets — with auto-scaling, observability, and enterprise-grade security.

OUR PROJECTS

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Global AI Agent Platform Deployment

Deployed a multi-region agent platform serving 2M+ monthly requests across 3 availability zones with 99.95% uptime and sub-200ms P95 latency.

JAN 2026

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GPU-Optimized Model Serving Pipeline

Built a model serving infrastructure with vLLM and TensorRT that reduced inference costs by 58% while improving throughput by 3.2x for a fintech client.

NOV 2025

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Edge AI Agent for Retail

Deployed lightweight AI agents to 400+ retail locations with edge compute, handling real-time customer queries with 50ms latency and offline fallback.

SEP 2025

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Multi-Agent Fleet for Insurance Claims

Orchestrated a fleet of 6 specialized agents (intake, triage, assessment, fraud detection, payout, communication) processing 12,000 claims monthly.

FEB 2026

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Zero-Downtime Agent Migration

Migrated a production AI agent platform from single-VM deployment to Kubernetes with zero downtime, reducing operational costs by 45%.

JUL 2025

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Auto-Scaling Agent for E-Commerce

Deployed a customer service agent that scales from 2 to 200 replicas during peak shopping events, handling 50x traffic spikes without degradation.

DEC 2025

OUR AI & LLM TECHNOLOGY STACK

Container & Orchestration

Docker
Kubernetes / EKS / GKE
Helm Charts
Kustomize
ArgoCD / FluxCD

Model Serving

vLLM
TGI (Text Generation Inference)
TensorRT-LLM
Triton Inference Server
BentoML

Cloud & Infrastructure

AWS (EKS, SageMaker, Bedrock)
Google Cloud (GKE, Vertex AI)
Azure (AKS, AI Studio)
Terraform / Pulumi

Observability

Prometheus / Grafana
OpenTelemetry
Datadog / New Relic
LangSmith / LangFuse

CI/CD & Security

GitHub Actions
GitLab CI
HashiCorp Vault
SOPS / Sealed Secrets
Network Policies

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FAQ SECTION

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