craft ai · 0 reviews

craft ai

Industrialize Generative AI with enterprise-grade MLOps and LLMOps governance

Machine Learning Software

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About craft ai

Craft AI is the first dedicated platform engineered for the industrialization of Generative and Responsible AI, designed for enterprises seeking to unlock the full potential of artificial intelligence at scale. The platform streamlines every phase of the AI lifecycle—from model development and training to deployment, monitoring, and governance—enabling data science teams to focus on driving business value rather than managing infrastructure complexity. Craft AI provides end-to-end MLOps and LLMOps capabilities, including experiment tracking, model versioning, automated testing, and production deployment orchestration. Its built-in governance and responsible AI framework ensures compliance, explainability, and ethical AI practices across all models. Through AiDOOS marketplace integration, enterprises gain seamless access to pre-configured deployment templates, certified model repositories, and expert governance patterns, accelerating time-to-production while maintaining enterprise-grade security and compliance standards.

Challenges It Solves

Organizations struggle to move generative AI models from research to production at scale
Lack of centralized governance frameworks for responsible and compliant AI deployment
Difficulty tracking, versioning, and managing multiple large language models across teams
Complex MLOps infrastructure requirements delay innovation and increase operational costs
Insufficient monitoring and governance of AI model performance and ethical outcomes in production

Faster time-to-production for generative AI models

Reduced operational complexity in AI model lifecycle

Improved model governance and compliance adherence

Use Cases

Enterprise Generative AI Deployment

Large organizations deploying multiple generative AI applications across departments can use Craft AI to standardize deployment processes, ensure governance compliance, and manage model lifecycle at enterprise scale.

85% Reduced deployment time and governance overhead

Financial Services AI Governance

Financial institutions require rigorous model governance and regulatory compliance. Craft AI provides audit trails, fairness monitoring, and explainability features essential for regulated AI deployments.

72% Enhanced compliance and reduced regulatory risk

Healthcare AI Model Management

Healthcare organizations managing clinical decision-support AI models benefit from Craft AI's responsible AI framework, ensuring transparency and trust in AI-assisted medical decisions.

68% Improved model transparency and clinical trust

Multi-Model LLM Orchestration

Organizations leveraging multiple large language models across teams can centralize management, version control, and deployment orchestration through Craft AI's unified platform.

79% Simplified multi-model management and scaling

Continuous AI Model Optimization

Data science teams can leverage Craft AI's monitoring and analytics to identify performance degradation, implement retraining pipelines, and optimize models continuously in production.

64% Sustained model performance and accuracy

Pricing

Pricing available on request

craft ai pricing is customized based on your team size, integrations, and requirements. AiDOOS will get you a scoped proposal — for free.

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Key Features

End-to-End MLOps & LLMOps

Complete AI lifecycle management from development to production

Unified platform eliminates fragmented tooling and reduces deployment cycles

Model Versioning & Experiment Tracking

Comprehensive tracking of model iterations and performance metrics

Teams maintain full reproducibility and audit trails for all model changes

Responsible AI & Governance Framework

Built-in compliance, fairness, and explainability monitoring

Ensures ethical AI practices and regulatory compliance across deployments

Automated Model Testing & Validation

Continuous quality assurance before production deployment

Reduces model failures in production and ensures consistent performance

Production Monitoring & Observability

Real-time tracking of model drift, performance, and anomalies

Enables rapid response to model degradation and data drift issues

Collaborative Model Development

Multi-team coordination and knowledge sharing across AI projects

Accelerates innovation through standardized workflows and best practices

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Enterprise Readiness

Role-Based Access Control (RBAC)

Audit Logging & Compliance Tracking

Model Governance & Explainability

Data Encryption & Secure Storage

Model Monitoring & Anomaly Detection

Integrations

8 total apps

Deploy and orchestrate AI models on Kubernetes clusters for scalable, containerized production environments

Integrate with MLflow for experiment tracking and model registry management

Support for TensorFlow model training, versioning, and deployment workflows

Native support for PyTorch models across development and production pipelines

Seamless integration with AWS SageMaker for cloud-native ML operations

Direct integration with Hugging Face model hub for pre-trained generative AI models

Orchestrate complex MLOps workflows and automated model retraining pipelines

Monitor model performance, infrastructure metrics, and operational health in real-time

AiDOOS Managed Deployment

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AiDOOS handles setup, CRM integration, SSO config, and user provisioning. Your team goes live — not your IT department.

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Adoption rate

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Time to value

Prerequisites

Configuration Options

Virtual Delivery Center · A new delivery category

A Virtual Delivery Center for craft ai

Pre-vetted experts and AI agents in the loop, assembled as a delivery pod. Pay in Delivery Units — universal pricing across roles, seniority, and tech stacks. No hiring, no contracting, no procurement cycle.

Plans from $2,000 — Starter Pack, 10 Delivery Units, 90 days
Refundable on unused Delivery Units, anytime — no questions asked
Re-delivery guarantee on acceptance miss
Pre-flight delivery sizing — you see the plan before you commit

Get a delivery plan for craft ai What’s a Virtual Delivery Center?

How a Virtual Delivery Center delivers craft ai

Outcome-based delivery via AiDOOS’s VDC model. Why VDC vs traditional consulting? →

Outcome-Based

Pay for results, not hours

Milestone-Driven

Clear deliverables at each phase

Expert Network

Access to certified specialists

Implementation Timeline

Discover

Requirements & assessment

Integrate

Setup & data migration

Validate

Testing & security audit

Rollout

Deployment & training

Optimize

Performance tuning

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Frequently Asked Questions

What is the primary difference between MLOps and LLMOps that Craft AI addresses?

MLOps focuses on traditional machine learning model lifecycle, while LLMOps extends this to large language models with unique challenges like prompt management, context handling, and fine-tuning. Craft AI provides unified tooling for both, with specialized features for generative AI governance and responsible AI monitoring.

How does Craft AI help with responsible AI and governance?

Craft AI includes built-in frameworks for fairness monitoring, bias detection, model explainability, and compliance tracking. These features ensure ethical AI practices and help organizations meet regulatory requirements, making it ideal for regulated industries when deployed through AiDOOS governance standards.

Can Craft AI integrate with our existing MLOps infrastructure?

Yes. Craft AI supports integration with popular ML frameworks (TensorFlow, PyTorch), deployment platforms (Kubernetes, AWS SageMaker), and workflow orchestration tools (Apache Airflow). AiDOOS marketplace provides pre-configured integration templates to accelerate setup.

What kind of organizations benefit most from Craft AI?

Enterprises with complex, multi-team AI deployments across departments or products benefit significantly. Financial services, healthcare, and technology companies find particular value in Craft AI's governance, compliance, and large-scale model management capabilities.

How does Craft AI handle model monitoring and drift detection?

Craft AI provides continuous monitoring of model performance, data drift, and prediction drift in production. Automated alerts trigger retraining pipelines when degradation is detected, ensuring consistent model accuracy and reliability over time.

Does Craft AI support multi-model deployment and orchestration?

Yes. Craft AI excels at managing multiple models across teams, providing centralized versioning, deployment orchestration, and monitoring. This is particularly valuable for organizations leveraging multiple LLMs or maintaining model portfolios across business units.