Transform your business with AI

Our specialized AI solution spans the entire lifecycle, from strategy to implementation, helping you achieve tangible business results.

Data/AI Strategy

Define your AI roadmap and business value

Data Engineering

Build foundations for AI-ready data platforms

Generative AI/Agents

Implement cutting-edge AI for content and insights.

AI Engineering

Turn AI models into production-ready systems

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Accelerate your digital transformation

Our comprehensive technology solutions help you build scalable, future-proof systems that drive innovation and deliver exceptional digital experiences.

Tech Strategy

Align technology with business objectives

Infrastructure & Platform

Build scalable, cloud-native tech foundations

Digital Product Engineering

Create high-quality digital experiences

View all tech Services

Our Solutions

Transform your business with AI

Our specialized AI solution spans the entire lifecycle, from strategy to implementation, helping you achieve tangible business results.

Data/AI Strategy

AI roadmaps with LLM integration and knowledge graphs

Data Engineering

Modern data stacks on AWS, GCP, and Azure

Generative AI/Agents

RAG systems, LLM fine-tuning, and intelligent agents

AI Engineering

Production ML pipelines and real-time inference

View all ai Cases

Accelerate your digital transformation

Our comprehensive technology solutions help you build scalable, future-proof systems that drive innovation and deliver exceptional digital experiences.

Tech Strategy

Architecture assessments and tech stack selection

Infrastructure & Platform

Kubernetes, microservices, and event-driven systems

Digital Product Engineering

Full-stack development with modern frameworks

View all tech Cases

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Our Solutions

Solutions

At Buildaz, we combine proven assets, modular tech, and repeatable playbooks to accelerate your AI journey, from exploration to impact.

Our Solutions

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Data/Agentic Platform

Buildaz DataStack

Our modular enterprise-grade data plataform to unify, govern, and operationalize your data.

Ingestion and processing capabilities
Data quality and observability
Scalable architecture
Enterprise-grade security

Buildaz AI Fabric

Accelerate AI development with our library of reusable ML components, custom agents, and ready-to-use APIs.

ML libraries for most use cases such as pricing, demand forecasting...
AI agents for automation & decision support
Ready-to-use APIs
Custom agent development

AI & Automation Discovery

Buildaz Playbooks

Battle-tested playbooks for discovering, validating, and scaling AI/automation use cases.

Data/AI Value Discovery – ML sprints, AI scoping frameworks
Automation Use Case Library – 400+ high-impact by function
Proven methodologies
Industry-specific templates

AI Maturity Assessment

Quickly benchmark your organization's AI readiness across people, tech, and data.

Identify gaps in your AI capabilities
Prioritize next steps
De-risk investments
Comprehensive benchmarking

AI Security Assessment

Comprehensive Security Audit

Complete security assessment covering all aspects of your AI systems, from model behavior to infrastructure protection.

Model & Data Risk Evaluation

Model behavior analysis: Test for model drift, unintended outputs, and susceptibility to adversarial inputs (e.g., prompt injection for LLMs).
Data leakage assessment: Check if sensitive or proprietary information has leaked into training data or outputs.
Training data provenance: Review data sources for compliance, licensing, and potential IP violations.
Bias & fairness audits: Identify discriminatory behavior or biased predictions using demographic or protected-class testing.

AI System Threat Modeling

Threat surface mapping: Identify entry points across APIs, model endpoints, data inputs, and user interactions.
Adversarial attack simulation: Test resilience against poisoning, evasion, and inference attacks.
Access & authorization review: Assess role-based access to AI systems, training data, and inference APIs.

Infrastructure & Deployment Security

Endpoint & API protection: Verify authentication, rate limiting, and input validation on model endpoints.
Model integrity verification: Ensure deployed models haven't been tampered with and match approved versions (e.g., hash checks, digital signatures).
MLOps pipeline hardening: Evaluate CI/CD practices for vulnerabilities (e.g., unsafe model retraining, unvetted code injection).

Compliance & Governance Review

Regulatory alignment check: Ensure AI systems align with frameworks like GDPR, ISO 42001, NIST AI RMF, or upcoming EU AI Act.
Audit trail & explainability: Assess whether decisions made by models can be logged, explained, and justified.
Data minimization & retention: Evaluate policies around data collection, retention, and deletion for model training and inference.

Risk Reporting & Recommendations

Risk scoring: Quantify vulnerabilities by severity and likelihood across model, infrastructure, and organizational dimensions.
Remediation roadmap: Provide prioritized recommendations and quick wins.
Security maturity benchmarking: Compare posture against industry best practices and peers.

Home /

Our Solutions

Solutions

At Buildaz, we combine proven assets, modular tech, and repeatable playbooks to accelerate your AI journey, from exploration to impact.

Our Solutions

Show:

Data/Agentic Platform

Buildaz DataStack

Our modular enterprise-grade data plataform to unify, govern, and operationalize your data.

Ingestion and processing capabilities
Data quality and observability
Scalable architecture
Enterprise-grade security

Buildaz AI Fabric

Accelerate AI development with our library of reusable ML components, custom agents, and ready-to-use APIs.

ML libraries for most use cases such as pricing, demand forecasting...
AI agents for automation & decision support
Ready-to-use APIs
Custom agent development

AI & Automation Discovery

Buildaz Playbooks

Battle-tested playbooks for discovering, validating, and scaling AI/automation use cases.

Data/AI Value Discovery – ML sprints, AI scoping frameworks
Automation Use Case Library – 400+ high-impact by function
Proven methodologies
Industry-specific templates

AI Maturity Assessment

Quickly benchmark your organization's AI readiness across people, tech, and data.

Identify gaps in your AI capabilities
Prioritize next steps
De-risk investments
Comprehensive benchmarking

AI Security Assessment

Comprehensive Security Audit

Complete security assessment covering all aspects of your AI systems, from model behavior to infrastructure protection.

Model & Data Risk Evaluation

Model behavior analysis: Test for model drift, unintended outputs, and susceptibility to adversarial inputs (e.g., prompt injection for LLMs).
Data leakage assessment: Check if sensitive or proprietary information has leaked into training data or outputs.
Training data provenance: Review data sources for compliance, licensing, and potential IP violations.
Bias & fairness audits: Identify discriminatory behavior or biased predictions using demographic or protected-class testing.

AI System Threat Modeling

Threat surface mapping: Identify entry points across APIs, model endpoints, data inputs, and user interactions.
Adversarial attack simulation: Test resilience against poisoning, evasion, and inference attacks.
Access & authorization review: Assess role-based access to AI systems, training data, and inference APIs.

Infrastructure & Deployment Security

Endpoint & API protection: Verify authentication, rate limiting, and input validation on model endpoints.
Model integrity verification: Ensure deployed models haven't been tampered with and match approved versions (e.g., hash checks, digital signatures).
MLOps pipeline hardening: Evaluate CI/CD practices for vulnerabilities (e.g., unsafe model retraining, unvetted code injection).

Compliance & Governance Review

Regulatory alignment check: Ensure AI systems align with frameworks like GDPR, ISO 42001, NIST AI RMF, or upcoming EU AI Act.
Audit trail & explainability: Assess whether decisions made by models can be logged, explained, and justified.
Data minimization & retention: Evaluate policies around data collection, retention, and deletion for model training and inference.

Risk Reporting & Recommendations

Risk scoring: Quantify vulnerabilities by severity and likelihood across model, infrastructure, and organizational dimensions.
Remediation roadmap: Provide prioritized recommendations and quick wins.
Security maturity benchmarking: Compare posture against industry best practices and peers.