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AI infrastructure services

We deploy ML models to production and make sure they stay up. CI/CD for your models, monitoring for drift, and alerts for when things break.

01
Service 01

AI/ML Deployment & Infrastructure

We set up model serving infrastructure with GPU optimization, auto-scaling, and CI/CD pipelines for your ML models. Cloud-native AI deployment on Kubernetes — from notebook to production.

Model serving infrastructure with GPU optimization & auto-scaling
CI/CD pipelines specifically designed for ML models
Cloud-native AI deployment (AWS SageMaker, GCP Vertex AI, Azure ML)
Kubernetes-based ML workload orchestration
Model versioning and artifact management
A/B testing and canary deployment for models

Tech Stack

KubernetesDockerAWS SageMakerGCP Vertex AIMLflowSeldon CoreKServeTerraform

How We Engage

2-Week Sprint
Deploy one model end-to-end
Ongoing Management
Full infrastructure ownership
Migration
Notebook → production pipeline
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02
Service 02

MLOps & AI Reliability

We set up monitoring for your models, detection for drift, and alerts for when things break. Automated retraining pipelines with SLA-driven reliability.

ML model monitoring & observability dashboards
Data drift detection & automated alerting
Automated model retraining pipelines
SLA-driven AI system reliability engineering
Model performance tracking and regression detection
Incident response playbooks for AI systems

Tech Stack

PrometheusGrafanaEvidently AIGreat ExpectationsAirflowKubeflowMLflow

How We Engage

MLOps Sprint
Full pipeline setup in 2 weeks
Reliability Retainer
Ongoing monitoring & tuning
Observability Audit
Assess & fix blind spots
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03
Service 03

Custom AI Agents & Tooling

AI-powered SRE agents for incident detection and auto-remediation. RAG-based internal knowledge systems, custom LLM integrations, and tooling that makes your team more productive.

AI-powered SRE agents (incident detection, auto-remediation)
RAG-based internal knowledge systems
Custom LLM integrations & fine-tuning
AI cost optimization tooling
Automated documentation and runbook generation
Intelligent alerting and triage systems

Tech Stack

LangChainLlamaIndexOpenAI APIPineconeChromaDBFastAPIPythonTypeScript

How We Engage

Agent Development
Custom-built for your workflow
RAG Sprint
Knowledge system in 2 weeks
LLM Consulting
Architecture & integration plan
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How we work

A proven process that gets AI systems to production — fast and reliably.

01

Audit

We assess your current AI infrastructure and identify reliability gaps, bottlenecks, and quick wins.

Free 30-min call
02

Architect

We design a production-grade AI infrastructure tailored to your scale, budget, and team capabilities.

1–2 weeks
03

Implement

We build, deploy, and test everything. You get working infrastructure, not a slide deck.

2–8 weeks
04

Operate

We monitor, optimize, and continuously improve. Your AI systems stay reliable as you scale.

Ongoing

Flexible pricing

Every project is different. Pick the model that fits your pace.

2-Week Sprint

Focused project with clear deliverables. Ship one thing, ship it right.

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Most Popular

Monthly Retainer

Ongoing infrastructure management. We become your AI infra team.

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Project-Based

Custom scope with milestone payments. For well-defined, larger builds.

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Ready to make your AI production-ready?

Get a free 30-minute AI infrastructure audit. We'll assess your setup and give you a concrete action plan.

Book Free AI Infra Audit