airweave-ai/airweave
Oct 2025 – Mar 2026
6 Months active
Languages Used
CSSJavaScriptPythonTypeScriptBashJSONXMLYAML
Technical Skills
API DevelopmentAPI IntegrationAsynchronous ProgrammingAuthenticationBackend DevelopmentCode Organization
Daan Manneke
PROFILE
Daan Manneke
Daan worked on the airweave-ai/airweave repository, delivering a resilient, multi-provider search platform with robust access control, scalable ingestion, and advanced LLM-driven retrieval. He engineered features such as entity-level permissions, continuous SharePoint sync, and a three-tiered search UI, leveraging Python, TypeScript, and Docker. His approach emphasized asynchronous programming, API design, and rigorous testing, integrating providers like Cerebras, Groq, and Vespa for hybrid semantic search. Daan’s work included modernizing embedding pipelines, improving observability, and streamlining deployment with CI/CD. The depth of his contributions is reflected in the breadth of features, bug fixes, and architectural improvements across backend and frontend systems.
Overall Statistics
Feature vs Bugs
59%Features
Repository Contributions
262Total
Bugs
64
Commits
262
Features
91
Lines of code
119,771
Activity Months6
Your Network
41 peopleSame Organization
@airweave.ai1
Shared Repositories
40
Aditya ArolkarMember
Alejandro TovarMember
Anuj GuptaMember
cassMember
cubic BotMember
Daan MannekeMember
Daan MannekeMember
Daniel StemanMember
Danny SheridanMember
Work History
March 2026
113 Commits • 52 Features
Mar 1, 2026March 2026 monthly summary for airweave: resilient, multi-provider search stack with enhanced tool-calling, observability, and UI improvements. The team delivered structured LLM-driven search across instant, classic, and agentic tiers with robust error handling, better budget control, and expanded provider support, enabling safer, scalable, and faster customer-facing results.
113 Commits • 52 Features
Mar 1, 2026March 2026 monthly summary for airweave: resilient, multi-provider search stack with enhanced tool-calling, observability, and UI improvements. The team delivered structured LLM-driven search across instant, classic, and agentic tiers with robust error handling, better budget control, and expanded provider support, enabling safer, scalable, and faster customer-facing results.
March 2026
February 2026
66 Commits • 17 Features
Feb 1, 2026February 2026 (airweave) delivered a robust modernization of the source ingestion and embedding stack, with strong improvements in data freshness, reliability, and developer productivity. The work established scalable source infrastructure, enabled incremental synchronization, and modernized embedding deployment. The changes emphasize business value through fresher data, lower operational risk, and easier maintainability.
February 2026
66 Commits • 17 Features
Feb 1, 2026February 2026 (airweave) delivered a robust modernization of the source ingestion and embedding stack, with strong improvements in data freshness, reliability, and developer productivity. The work established scalable source infrastructure, enabled incremental synchronization, and modernized embedding deployment. The changes emphasize business value through fresher data, lower operational risk, and easier maintainability.
January 2026
47 Commits • 12 Features
Jan 1, 2026January 2026 performance and delivery highlights: - Implemented a comprehensive Access Control System across the Airweave platform, including a membership database, core access module, generic action/dispatchers, and integration touchpoints for Vespa destination, search filters, and SharePoint 2019 V2 sources, accompanied by full documentation. This enables fine-grained, entity-level permissions and scalable access governance across destinations. - Expanded Vespa integration with VespaContent and embedding enhancements: introduced VespaContent model, nested struct support, and Matryoshka dimension handling in embedding pipelines; added VespaChunkEmbedProcessor for external chunking/embedding, enabling entity-as-document storage and 1:1 chunk-to-entity mappings for Vespa. - Strengthened search capabilities and cross-destination query interpretation: made Vespa the default search destination, enabled query interpretation for all vector destinations, translated interpretation filters to valid YQL, and fixed multi-schema search and bulk delete response parsing for reliability and correctness. - Refactored and hardened the embedding pipeline: renamed ChunkEmbedProcessor to QdrantChunkEmbedProcessor, added VESPA_CHUNKS_AND_EMBEDDINGS processing, and updated Vespa schema to support direct tensor assignment; ensured chunk/embedding fields live inside the schema to reflect external computation. - Improved reliability, testing, and observability: faster asynchronous Vespa deletion, improved logging around chunking/embedding and search flows, extensive E2E smoke tests for filters, and tooling upgrades (pytest-asyncio 0.24+ and loop_scope fixes).
47 Commits • 12 Features
Jan 1, 2026January 2026 performance and delivery highlights: - Implemented a comprehensive Access Control System across the Airweave platform, including a membership database, core access module, generic action/dispatchers, and integration touchpoints for Vespa destination, search filters, and SharePoint 2019 V2 sources, accompanied by full documentation. This enables fine-grained, entity-level permissions and scalable access governance across destinations. - Expanded Vespa integration with VespaContent and embedding enhancements: introduced VespaContent model, nested struct support, and Matryoshka dimension handling in embedding pipelines; added VespaChunkEmbedProcessor for external chunking/embedding, enabling entity-as-document storage and 1:1 chunk-to-entity mappings for Vespa. - Strengthened search capabilities and cross-destination query interpretation: made Vespa the default search destination, enabled query interpretation for all vector destinations, translated interpretation filters to valid YQL, and fixed multi-schema search and bulk delete response parsing for reliability and correctness. - Refactored and hardened the embedding pipeline: renamed ChunkEmbedProcessor to QdrantChunkEmbedProcessor, added VESPA_CHUNKS_AND_EMBEDDINGS processing, and updated Vespa schema to support direct tensor assignment; ensured chunk/embedding fields live inside the schema to reflect external computation. - Improved reliability, testing, and observability: faster asynchronous Vespa deletion, improved logging around chunking/embedding and search flows, extensive E2E smoke tests for filters, and tooling upgrades (pytest-asyncio 0.24+ and loop_scope fixes).
January 2026
December 2025
17 Commits • 4 Features
Dec 1, 2025December 2025 monthly summary for airweave project focused on delivering scalable vector-based search capabilities, stabilizing admin workflows, and enabling robust data evaluation pipelines. Key business outcomes include faster, more accurate cross-destination search results, reduced admin errors, and a scalable evaluation/storage workflow, all while expanding Jira test-management alignment.
December 2025
17 Commits • 4 Features
Dec 1, 2025December 2025 monthly summary for airweave project focused on delivering scalable vector-based search capabilities, stabilizing admin workflows, and enabling robust data evaluation pipelines. Key business outcomes include faster, more accurate cross-destination search results, reduced admin errors, and a scalable evaluation/storage workflow, all while expanding Jira test-management alignment.
November 2025
2 Commits • 1 Features
Nov 1, 2025November 2025 — Focused on refining token-management for OAuth sources in airweave. Delivered an OAuth-Based Token Manager Initialization feature that creates token managers only for sources that support token refresh, improving correctness, efficiency, and business value by preventing unnecessary token handling for non-refreshable OAuth sources. Also addressed core initialization bugs to ensure robust behavior.
2 Commits • 1 Features
Nov 1, 2025November 2025 — Focused on refining token-management for OAuth sources in airweave. Delivered an OAuth-Based Token Manager Initialization feature that creates token managers only for sources that support token refresh, improving correctness, efficiency, and business value by preventing unnecessary token handling for non-refreshable OAuth sources. Also addressed core initialization bugs to ensure robust behavior.
November 2025
October 2025
17 Commits • 5 Features
Oct 1, 2025In Oct 2025, the airweave team delivered a set of reliability, compatibility, and performance improvements across OCR processing, data retrieval, search, and data ingestion pipelines. The work focused on increasing uptime, data integrity, and throughput while reducing failure modes in edge cases. Key cross-cutting improvements include enhanced retry and backoff strategies, improved data compatibility with legacy records, and safer, more scalable chunking and scheduling. The following achievements reflect concrete business value:
October 2025
17 Commits • 5 Features
Oct 1, 2025In Oct 2025, the airweave team delivered a set of reliability, compatibility, and performance improvements across OCR processing, data retrieval, search, and data ingestion pipelines. The work focused on increasing uptime, data integrity, and throughput while reducing failure modes in edge cases. Key cross-cutting improvements include enhanced retry and backoff strategies, improved data compatibility with legacy records, and safer, more scalable chunking and scheduling. The following achievements reflect concrete business value:
Activity
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Quality Metrics
Correctness94.4%
Maintainability88.4%
Architecture91.0%
Performance87.2%
AI Usage38.4%
Skills & Technologies
Programming Languages
BashCSSJSONJavaScriptMarkdownPythonTypeScriptXMLYAMLYQL
Technical Skills
AI DevelopmentAI integrationAPI DesignAPI DevelopmentAPI DocumentationAPI IntegrationAPI designAPI developmentAPI integrationAPI testingAlembicAlembic migrationAsynchronous ProgrammingAuthenticationBackend Development
Repositories Contributed To
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