The Toolkit for AI R&D
Build, experiment, and iterate with confidence. Pipelines provides the infrastructure to move fast—from data collection and human evaluation to confident deployments.
Jan 28, 2025·4 min read
The ecosystem for AI
R&D
Build, experiment, and scale your AI research with confidence. Pipelines gives your team the infrastructure to move fast without breaking things.
Built by a team from
MercorMetaDoorDash
Who is Pipelines for?
Designed for teams that treat AI as an engineering discipline.
Vertical AI Startups
Building specialized models (legal, medical, financial) that demand expert-level feedback.
Enterprise Product Teams
Integrating GenAI into core products and needing rigorous safety and quality checks before deployment.
Foundation Model Labs
Scaling RLHF and fine-tuning workflows without diverting engineering talent to build internal tools.
The Shift
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Building reliable AI products requires more than just models. It requires infrastructure. Yet, modern teams are stuck patching together fragmented tools.
AI Development Challenges
Most AI teams operate with scattered data: human annotations, synthetic generations, and legacy datasets trapped in messy spreadsheets with no unified structure. Evaluation is ad hoc - inconsistent benchmarks, manual spot-checks, no reproducibility. And when it's time to iterate, scaling requires bespoke scripts and pipeline rewrites, turning what should be rapid experimentation into weeks of engineering overhead. The result: a development cycle that's slow, brittle, and untrustworthy at production scale.
The core problem isn't talent or compute - it's infrastructure. Teams waste 60% of their time on data wrangling, glue code, and eval plumbing instead of training better models. Without dedicated tooling, every experiment becomes a systems-engineering project. The ecosystem needs a platform that collapses this complexity - so teams can run 10x more experiments, trust their results, and ship models that actually work in production.
Our Solution
Structured Data Collection
Design custom task workflows with strong schema guarantees, built-in versioning, and structured exports. Every annotation, label, and judgment follows a consistent, machine-readable format across any modality.
Evaluation You Can Trust
Built to Scale Fast
Core Capabilities
Everything you need to accelerate research
Design structured workflows to gather datasets and evaluate models, then explore results instantly through built-in dashboards - no export-and-analyze loop required.
Flexible Data Collection
Design multi-step task workflows with branching logic, structured schemas, and versioned definitions. Supports any modality from text and images to rankings and free-form feedback.
The Vision
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Just as CI/CD brought discipline to software releases, Pipelines brings discipline to AI development.
We are building the standard for:
- Dataset Versioning & Lineage
- Fine-tuning Orchestration
- Active Learning Loops
- Agentic Training Workflows
Our Philosophy
AI development should be accessible. The best AI systems are built through iteration—collecting feedback, evaluating performance, and continuously improving.
Models become truly capable when they learn from human expertise. Whether it's labeled data, preference feedback, or domain-specific evaluation, humans remain irreplaceable in the development loop.
From the Blog
View all postsInsights & Updates
Engineering5 min read
Closing the Loop: From Evaluation to Improvement
How to move beyond simple evaluation to a continuous cycle of improvement with dataset versioning, fine-tuning orchestration, and regression detection.
Jan 20, 2025
Vision6 min read
Why We Built Pipelines: The Coordination Layer for AI
Modern AI teams face a fragmented path from idea to production. Pipelines is the coordination layer that unifies data, evaluation, and training.
Jan 15, 2025
Get Started
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We partner closely with ambitious teams to refine the platform around real-world production needs.
Design Partners Receive:
- White-glove onboarding and workflow optimization.
- Priority access to custom components and integrations.
- Direct channel to engineering for feature requests.
Contact directly:
contact@buildpipelines.com