Technology
Factored AI builds and scale production-grade AI and data platforms for technology companies with demanding performance, reliability, and talent standards.
Elite AI And Data Engineering Accelerating Your Roadmap
01
AI Infrastructure & MLOps Engineering
Faster model deployment cycles with higher reliability in production.
Designed end-to-end ML platforms covering training, evaluation, deployment, monitoring, and governance across cloud environments.
Designed end-to-end ML platforms covering training, evaluation, deployment, monitoring, and governance across cloud environments.
02
Data Infrastructure & Developer Enablement
Reduced friction for product and data teams while improving data quality and trust.
Built scalable data architectures, analytics layers, and self-serve tooling that integrate directly with engineering workflows.
Built scalable data architectures, analytics layers, and self-serve tooling that integrate directly with engineering workflows.
03
Applied AI for Product Intelligence
Enabled AI-powered features to ship faster without compromising quality or safety.
Embedded ML, NLP, and GenAI capabilities into core product surfaces with strong evaluation, guardrails, and observability.
Embedded ML, NLP, and GenAI capabilities into core product surfaces with strong evaluation, guardrails, and observability.
Case Studies & Proven Impact
AI Platform Engineering for Production ML Systems
Ship ML models to production faster without breaking reliability.
- Product teams struggled to operationalize models consistently across environments.
- Built standardized ML platform components for training, deployment, monitoring, and rollback across cloud infrastructure.
- Faster release cycles, improved system stability, and reduced operational overhead for engineering teams.
Data Governance & Access Control Framework
Enable secure data access without slowing down development.
- Rapid data growth created governance risk and access bottlenecks.
- Implemented fine-grained data access controls, metadata management, and audit-ready pipelines.
- Improved compliance posture while enabling faster experimentation for product and analytics teams.
Developer-Focused Analytics & Observability Platform
Give engineers real-time visibility into data and system behavior.
- Engineers lacked reliable observability across data pipelines and services.
- Built real-time analytics and monitoring layers integrated directly into engineering workflows.
- Faster incident resolution, higher system reliability, and improved developer productivity.
Scalable Feature Stores & Model Serving Infrastructure
Serve consistent features and predictions across products at scale.
- Inconsistent feature definitions caused model drift and unreliable predictions.
- Designed centralized feature stores and low-latency model serving infrastructure.
- Improved model consistency, reduced rework, and faster onboarding of new ML use cases.
GenAI Enablement for Product Teams
Safely embed generative AI into customer-facing products.
- Product teams wanted GenAI features but lacked evaluation, safety, and scalability controls.
- Built GenAI pipelines with prompt management, evaluation harnesses, and monitoring guardrails.
- Faster GenAI feature launches with reduced risk and higher confidence in production behavior.
Three Engagement Models
Embedded Engineers
Elite, dedicated engineers who onboard quickly, are embedded in your team, and are managed by your stakeholders.
Managed Services
End-to-end AI and data solutions designed, managed, and scaled by Factored to drive measurable ROI.
Advisory in AI, ML, and Data
Senior architects guide feasibility, prioritization, and strategy with expert insight to de-risk critical decisions, solve challenges and drive competitive advantage.
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Elite engineers ready to accelerate your roadmap.
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