Synapse is a collaborative AI data workspace that connects pipelines, notebooks, and vector stores for analytics and retrieval. Ingest, transform, and index data, then build chat and search on top. With orchestration, permissions, and observability, teams deliver reliable insights without stitching fragile scripts. Lineage and metrics keep changes visible so trust grows release by release.
Stream or batch data from warehouses, lakes, and apps, then transform with declarative steps. Connectors handle auth and schema drift gracefully. Because ingestion is dependable, teams focus on models and UX instead of glue code. Lineage tracks sources and changes, which shortens debugging. The result is steady flow from systems into features that products and analysts can trust over time.
Work in notebooks with access to curated datasets and shared features. Train and evaluate models, then promote artifacts with version tags. With reproducible environments, experiments compare fairly and collaboration feels natural. Feature stores keep definitions consistent across teams. This discipline avoids drift and protects accuracy when models retrain on fresh data across regions.
Create embeddings, manage indexes, and tune recall with filters and re-ranking. Hybrid search mixes keywords and vectors so results remain precise. With instrumentation for quality, teams spot gaps and refine prompts or data quickly. Retrieval becomes predictable and explainable, which builds trust for chat, assist, and recommendation use cases across roles, devices, and locales.
Schedule jobs, set SLAs, and alert on failures or anomalies. Logs, traces, and lineage unite around runs so owners see cause and effect. Because operations are visible, teams catch breakage early and prove reliability with metrics. This observability keeps pipelines healthy and gives stakeholders confidence that insights and features will be available when needed and audited.
SSO, roles, and column-level controls protect sensitive fields, while audit logs record queries and changes. Policies travel with data through pipelines into indexes and apps. With governance built in, programs scale safely. Compliance teams verify access quickly, and developers ship faster because approvals rely on clear evidence rather than manual spreadsheets, tickets, and long email threads.
Best for data, product, and platform teams building AI features on company data. With connectors and pipelines, collaborative notebooks, vector retrieval, robust orchestration, and governance, Synapse turns raw sources into dependable experiences. People move from ingestion to insight quickly, while reliability and compliance remain visible for leadership, customers, and auditors.
Synapse replaces one-off ETL, brittle notebooks, and ungoverned indexes with a unified, observable workflow. Data flows reliably, features stay consistent, and retrieval remains explainable. Because permissions and lineage are native, risk drops and approvals speed up. Outcomes include faster iteration, cleaner audits, and AI products that stay accurate as sources evolve over time.
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