FAQ
Your Questions. Answered.
Common questions about AI implementation, validation methodologies, pricing, and our engagement process.
General
Checksum Labs is an AI research and development company specializing in validated machine learning, automated quality assurance, and intelligent data verification. We combine academic rigor with enterprise engineering to deliver AI solutions you can trust.
Our validation-first approach sets us apart. While other companies focus on building AI quickly, we ensure every model is thoroughly tested, explainable, and production-ready. We treat validation as seriously as innovation.
We serve FinTech, Healthcare, E-commerce, Manufacturing, and Enterprise SaaS. Our expertise in regulatory compliance makes us particularly suited for regulated industries like financial services and healthcare.
Services
We offer end-to-end AI services including AI Strategy & Consulting, Machine Learning Solutions, NLP, Computer Vision, Generative AI, Data Engineering, Business Intelligence, MLOps, and our signature AI Model Validation service.
Yes, we offer AI validation and testing services for existing models. We can audit your current AI systems, identify issues, implement monitoring, and help improve reliability without rebuilding from scratch.
Both. We tailor our approach to your needs. Sometimes pre-trained models with fine-tuning are the best solution; other times, custom model development is required. We'll recommend the right approach for your use case.
Process & Methodology
Our 6-stage process ensures quality at every step: Research & Requirements, Data Validation, Model Development, Rigorous Testing, Deployment & Monitoring, and Continuous Validation. Validation isn't an afterthought—it's built into every stage.
Project timelines vary based on scope. A proof-of-concept might take 4-6 weeks. A full enterprise implementation typically takes 3-6 months. We provide detailed timelines during the scoping phase.
We're SOC 2 and ISO 27001 compliant. We can work with your data on-premises, in your cloud, or in our secure environment. For healthcare, we're HIPAA compliant. Data security is non-negotiable.
Pricing & Engagement
We offer flexible pricing models: project-based for defined scope, retainer for ongoing work, and capacity-based for continuous development. We'll recommend the model that best fits your needs during the initial consultation.
Yes, we often start with a focused PoC to demonstrate value before committing to a larger engagement. This reduces risk and helps both parties validate the approach.
After an initial consultation, we scope the project, agree on deliverables and timeline, then begin with discovery and requirements. We work in agile sprints with regular check-ins. You'll have visibility into progress throughout.
Technical
We use industry-leading tools: TensorFlow, PyTorch, and Scikit-learn for ML; AWS, Azure, and GCP for cloud; Spark and Airflow for data engineering; MLflow and Kubeflow for MLOps. We choose the right tool for each project.
Yes, integration is a core capability. We build APIs, work with legacy systems, and ensure our AI solutions fit into your existing infrastructure with minimal disruption.
Yes, we offer various support tiers from basic monitoring to 24/7 enterprise support. Most clients choose ongoing engagement for model monitoring, retraining, and continuous improvement.