{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_beloga","slug":"beloga","name":"Beloga","type":"product","url":"https://www.beloga.xyz","page_url":"https://unfragile.ai/beloga","categories":["automation"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_beloga__cap_0","uri":"capability://data.processing.analysis.multi.source.data.unification.with.real.time.sync","name":"multi-source data unification with real-time sync","description":"Beloga aggregates data from multiple disconnected applications (e.g., Slack, email, project management tools, document stores) into a unified view using API connectors and webhook-based real-time synchronization. The system maintains a normalized data model that maps heterogeneous schemas from different sources into a common representation, enabling cross-app queries and unified search without requiring users to switch between platforms.","intents":["consolidate information scattered across 5+ different tools into a single searchable interface","eliminate manual copy-paste workflows when pulling data from multiple sources for research or analysis","see real-time updates from all connected apps without opening each one individually","reduce context-switching overhead for knowledge workers managing multiple data silos"],"best_for":["small research teams (2-20 people) using 4+ disparate tools","knowledge workers managing cross-functional projects with data in multiple platforms","teams without dedicated data engineering resources to build custom ETL"],"limitations":["API rate limits from source applications may cause sync delays (typically 5-30 second latency)","schema mapping is likely manual or template-based, not fully automatic — custom integrations may require configuration","no built-in conflict resolution for duplicate or contradictory data across sources","limited to applications with public APIs; proprietary or legacy systems may not be supported"],"requires":["API credentials or OAuth tokens for each connected application","stable internet connection for continuous webhook polling","applications must support API access (not all SaaS tools do)"],"input_types":["API responses (JSON, XML)","webhook payloads","structured data from connected apps"],"output_types":["unified data view (likely JSON or structured format)","search results across all sources","real-time notifications of changes"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_1","uri":"capability://search.retrieval.ai.powered.cross.app.search.and.retrieval","name":"ai-powered cross-app search and retrieval","description":"Beloga uses semantic search or embedding-based retrieval to find relevant information across all connected applications using natural language queries, rather than requiring exact keyword matching or manual navigation. The system likely embeds documents, messages, and structured data from each source into a vector space, then ranks results by semantic relevance and recency, surfacing context from multiple apps in a single result set.","intents":["search for information across all connected apps using a single natural language query","find related context from different tools without knowing which app contains the answer","retrieve historical data and conversations across platforms in one place","discover connections between data in different silos (e.g., a Slack mention related to a Jira ticket)"],"best_for":["research teams needing to correlate information across multiple sources","knowledge workers who frequently search for context across tools","teams with high information volume (100+ documents/messages daily)"],"limitations":["embedding quality depends on the LLM used; generic embeddings may miss domain-specific relevance","no apparent support for full-text search fallback if semantic search fails","embedding costs scale with data volume; large teams may face performance degradation","search results may include stale or archived data without explicit filtering"],"requires":["connected data sources with sufficient content to embed","API access to embedding model (likely OpenAI, Cohere, or self-hosted)","vector database backend (e.g., Pinecone, Weaviate, Milvus)"],"input_types":["natural language queries","text from documents, messages, and structured data"],"output_types":["ranked list of results with source attribution","snippets or excerpts from matched documents","metadata (timestamp, app source, relevance score)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_2","uri":"capability://text.generation.language.ai.generated.insights.and.summaries.from.unified.data","name":"ai-generated insights and summaries from unified data","description":"Beloga generates automated summaries, highlights, and insights from aggregated data across connected applications using LLM-based analysis. The system likely batches recent data from multiple sources, sends it to an LLM with a prompt tailored to research or team workflows, and returns synthesized insights (e.g., 'key decisions made this week', 'unresolved blockers across projects', 'trends in team communication'). Results are cached or scheduled to avoid redundant API calls.","intents":["get a daily or weekly summary of what happened across all connected apps without reading each one","identify key decisions, blockers, or trends without manual analysis","surface actionable insights from scattered data (e.g., 'these two projects have conflicting timelines')","generate reports or briefings for stakeholders from unified data"],"best_for":["team leads or managers needing quick status updates across multiple tools","research teams synthesizing findings from multiple sources","small teams (under 50 people) where manual synthesis is still feasible"],"limitations":["LLM-generated insights may hallucinate or misinterpret context without human review","no apparent customization of insight types or focus areas per team or user","summarization quality degrades with very large data volumes (100+ messages/documents per day)","insights are likely generated on a fixed schedule (daily/weekly) rather than on-demand, limiting real-time responsiveness"],"requires":["sufficient data volume from connected sources to generate meaningful insights","LLM API access (likely OpenAI GPT-4 or similar)","scheduling infrastructure for periodic batch processing"],"input_types":["aggregated text from multiple sources (messages, documents, tickets)","metadata (timestamps, authors, source app)"],"output_types":["natural language summaries","bullet-point highlights","structured insights (JSON or formatted text)","reports or briefings"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_3","uri":"capability://tool.use.integration.app.connector.framework.with.schema.mapping","name":"app connector framework with schema mapping","description":"Beloga provides a framework for connecting external applications via APIs, webhooks, or pre-built connectors, with a schema mapping layer that translates heterogeneous data models into a normalized internal representation. The system likely uses a connector registry (similar to Zapier or Airbyte) with templates for popular apps, and allows custom field mapping for less common integrations. Data flows through a transformation pipeline that normalizes timestamps, user IDs, and other common fields across sources.","intents":["add a new data source to Beloga without custom development","map fields from a connected app to Beloga's internal schema","maintain data consistency across multiple sources with different field naming conventions","extend Beloga to support custom or proprietary applications"],"best_for":["teams with 4-8 connected applications (sweet spot before complexity explodes)","non-technical users who need to add integrations without coding","organizations with custom or legacy systems requiring bespoke connectors"],"limitations":["pre-built connectors likely cover only popular apps (Slack, Jira, Notion, etc.); niche tools require custom work","schema mapping is probably manual or template-based, not fully automatic — requires understanding of both source and target schemas","no apparent support for complex transformations (e.g., aggregations, joins across sources)","connector maintenance burden falls on Beloga team; breaking API changes in source apps may cause outages"],"requires":["API documentation for the application being connected","API credentials or OAuth tokens","understanding of the source app's data model"],"input_types":["API endpoints","webhook URLs","OAuth credentials","field mapping configuration (JSON or UI-based)"],"output_types":["normalized data in Beloga's internal schema","transformation logs and error reports"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_4","uri":"capability://automation.workflow.real.time.notification.and.alert.system","name":"real-time notification and alert system","description":"Beloga monitors connected data sources for changes and generates notifications or alerts based on user-defined rules or AI-detected anomalies. The system likely uses webhook listeners to detect events in real-time, evaluates them against rule engines or LLM-based anomaly detection, and routes notifications to users via email, in-app alerts, or Slack. Rules can be simple (e.g., 'notify me when a Jira ticket is assigned to me') or complex (e.g., 'alert if multiple projects report blockers on the same dependency').","intents":["get notified immediately when important events occur across connected apps","set up custom alerts based on specific conditions or patterns","reduce notification fatigue by filtering or aggregating alerts intelligently","detect anomalies or unusual patterns in team activity across tools"],"best_for":["teams needing real-time visibility into cross-app events","managers or leads who need to stay informed without constant manual checking","research teams tracking specific data points across multiple sources"],"limitations":["rule engine is likely limited to simple conditions; complex logic may require custom development","notification delivery latency depends on webhook reliability of source apps (typically 1-30 seconds)","no apparent support for notification deduplication or aggregation, risking alert fatigue","AI-based anomaly detection may require training data or manual tuning per team"],"requires":["connected data sources with webhook support","notification delivery infrastructure (email, Slack API, etc.)","rule definition (UI-based or JSON configuration)"],"input_types":["webhook events from connected apps","rule definitions (conditions, actions)","user preferences (notification channels, frequency)"],"output_types":["notifications (email, Slack, in-app)","alert logs and history","rule execution reports"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_5","uri":"capability://text.generation.language.collaborative.workspace.with.shared.context","name":"collaborative workspace with shared context","description":"Beloga provides a shared workspace where team members can view, discuss, and act on unified data from connected apps. The workspace likely includes a feed or dashboard showing recent activity across sources, comment threads for collaboration, and quick-access panels for each connected app. Users can pin important items, create collections or projects, and share context with teammates without requiring them to access the original apps.","intents":["collaborate on research or analysis using data from multiple sources in one place","share context with teammates without sending links to multiple apps","create a shared view of project status across tools","discuss findings or decisions with full context visible to all participants"],"best_for":["small to medium teams (5-50 people) with shared research or project goals","distributed teams that benefit from asynchronous collaboration","teams wanting to reduce context-switching and tool fragmentation"],"limitations":["no apparent support for real-time collaborative editing (unlike Notion or Google Docs)","permission model is likely simple (shared workspace access) without granular per-item controls","workspace organization is probably limited to basic collections or projects; no advanced taxonomy or tagging","no apparent version history or audit trail for changes made in the workspace"],"requires":["team members with Beloga accounts","connected data sources to populate the workspace","stable internet connection for real-time updates"],"input_types":["data from connected apps","user comments and annotations","workspace configuration (collections, pins, sharing)"],"output_types":["shared workspace view","activity feed","comment threads","exported reports or collections"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_beloga__cap_6","uri":"capability://safety.moderation.permission.and.access.control.across.unified.data","name":"permission and access control across unified data","description":"Beloga manages permissions for accessing unified data, likely inheriting or mapping access controls from source applications. The system probably supports role-based access control (RBAC) with roles like 'viewer', 'editor', or 'admin', and may enforce source-level permissions (e.g., if a user lacks access to a Jira project, they cannot see tickets from that project in Beloga). Permission inheritance and conflict resolution across multiple sources is likely handled via a centralized policy engine.","intents":["ensure users only see data they have permission to access in the source apps","grant team members access to specific collections or projects in Beloga","manage permissions at scale without manually configuring each source app","audit who accessed what data and when"],"best_for":["teams with sensitive data requiring strict access controls","organizations with compliance requirements (SOC 2, HIPAA, etc.)","teams using multiple apps with different permission models"],"limitations":["permission model is likely simple (workspace-level or collection-level) without item-level granularity","no apparent support for attribute-based access control (ABAC) or dynamic policies","permission inheritance from source apps may be incomplete or lag behind source system changes","no built-in audit logging or compliance reporting"],"requires":["source app credentials with sufficient permissions to read access control lists","Beloga workspace configuration (roles, members)"],"input_types":["source app permission models","Beloga role assignments","user identity and group information"],"output_types":["access control decisions (allow/deny)","permission audit logs","user role assignments"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["API credentials or OAuth tokens for each connected application","stable internet connection for continuous webhook polling","applications must support API access (not all SaaS tools do)","connected data sources with sufficient content to embed","API access to embedding model (likely OpenAI, Cohere, or self-hosted)","vector database backend (e.g., Pinecone, Weaviate, Milvus)","sufficient data volume from connected sources to generate meaningful insights","LLM API access (likely OpenAI GPT-4 or similar)","scheduling infrastructure for periodic batch processing","API documentation for the application being connected"],"failure_modes":["API rate limits from source applications may cause sync delays (typically 5-30 second latency)","schema mapping is likely manual or template-based, not fully automatic — custom integrations may require configuration","no built-in conflict resolution for duplicate or contradictory data across sources","limited to applications with public APIs; proprietary or legacy systems may not be supported","embedding quality depends on the LLM used; generic embeddings may miss domain-specific relevance","no apparent support for full-text search fallback if semantic search fails","embedding costs scale with data volume; large teams may face performance degradation","search results may include stale or archived data without explicit filtering","LLM-generated insights may hallucinate or misinterpret context without human review","no apparent customization of insight types or focus areas per team or user","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.2833333333333333,"quality":0.63,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.714Z","last_scraped_at":"2026-04-05T13:23:42.562Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=beloga","compare_url":"https://unfragile.ai/compare?artifact=beloga"}},"signature":"2EqrkO9rPOr1qTAEAx9jZaRzWbFqNRvN3aNitKdQpIqZ3096UiL48OPVHeaRfzX86ekAF2QyMa2W7m5+BausDQ==","signedAt":"2026-06-21T02:49:10.547Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/beloga","artifact":"https://unfragile.ai/beloga","verify":"https://unfragile.ai/api/v1/verify?slug=beloga","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}