Building AI Assistants with Tool Calling
Learn how to create AI assistants that can call custom functions, webhooks, and MCP tools to extend their capabilities beyond simple chat.
Read More →Blog
Insights on AI, infrastructure, and European tech
Automatic Execution Tracking for Python Functions
How SINAS uses AST injection to automatically track nested function calls and build complete execution trees without manual instrumentation.
Read More →Introducing the Ontology System
Connect to external databases with three operational modes: external query, synced, and self-managed. Build semantic data layers without data duplication.
Read More →AI-Powered Document Auto-Tagging
Use AI assistants to automatically tag documents with custom metadata. Set up tagger rules and run bulk operations on entire folders.
Read More →Granular Permissions with Hierarchical Scopes
Understanding SINAS's permission system: how :own, :group, and :all scopes work together with wildcard patterns for fine-grained access control.
Coming SoonHow FinTech Startup Built RAG Applications
A European fintech company used SINAS's context store and AI assistants to build a customer support system with semantic memory and document retrieval.
Coming SoonWebhooks, Schedules, and Function Orchestration
Building event-driven workflows with SINAS: combine webhooks for HTTP triggers, schedules for cron jobs, and nested function calls for complex logic.
Coming SoonEmail Automation with Templates and Webhooks
Set up email inboxes that trigger functions on receipt, use Jinja2 templates for sending, and build complete email workflows.
Coming SoonContext Injection for Smarter AI Assistants
Use the context store to inject relevant information into AI conversations. Learn about namespaces, relevance scoring, and automatic context selection.
Coming Soon