Back to list

Team AI Agent Integration with Langbase

Let teams invoke Langbase AI agents through natural language in Slack, Teams, or Discord, triggering workflows and pulling insights instantly. Enhance your Langbase workflows with AI-powered automation in Slack, Teams, and Discord.

Chat-Driven Langbase Agent Workflows
Let teams invoke Langbase AI agents through natural language in Slack, Teams, or Discord, triggering workflows and pulling insights instantly.
Schedule Automated Reports with Langbase
Deliver AI-powered summaries and analytics from Langbase agents on a daily or weekly schedule, directly into team channels.
Instant Contextual Q&A in Your Team Chat
Enable teams to query Langbase-powered knowledge with AI agents, retrieving real-time answers from custom RAG models—no app-switching.
Collaborative AI Agent Memory Management
Teams can update, reset, or fetch Langbase AI agent memory and histories together, directly from Slack using simple AI-powered commands.
Automate Your Langbase Workflows with AIStart your free trial and see the difference in minutes.

Langbase Integration Thumbnail

Seamless collaboration and automation lie at the heart of tomorrow’s smart teams. By combining Langbase’s robust AI agent infrastructure with Runbear’s intuitive chat-based platform, teams transform the way they operate. Now, AI agents built on Langbase can join your team's daily conversations in Slack, Teams, or Discord—bringing AI-powered workflows, instant knowledge retrieval, and scheduled automation right to where you work.

About Langbase

Langbase is a developer-friendly, serverless AI platform designed to make building and scaling custom AI agents faster and easier. It abstracts away complex frameworks, turning chat prompts into production-grade AI agents through features like Command.new, Pipe Agents, and native support for over 600+ LLMs. With integrated RAG memory, powerful workflow orchestration, and universal API endpoints, Langbase is chosen by fast-moving engineering teams and tech-forward enterprises looking to put AI at the core of their app infrastructure and internal tools. Teams use Langbase to rapidly experiment, deploy, and operationalize AI solutions without managing servers or reinventing the wheel—making it a go-to for organizations that want production reality, not just AI demos.

Core users include AI/ML engineers, product teams, and organizations prioritizing agility and innovation in their internal and customer-facing workflows.

Use Cases in Practice

With the Langbase + Runbear integration, teams get the best of both worlds: AI agents tailored to their business logic, and frictionless, chat-first access for every employee. For example, an engineering team can build a Langbase workflow that summarizes support tickets—then, with Runbear, anyone in support can simply ask the agent in Slack for an update. Operations teams receive scheduled insights without ever writing code, while product leads collaborate in real time on agent memory or Q&A tasks directly in chat. This shift empowers teams to automate routine work, access actionable data, and maintain vital context—all without switching apps or relying solely on developer intervention. These use cases mirror what we highlight in guides like Simplify Your Business Analytics and Transform Your Team’s Daily Workflow with Smart Scheduling Powered by MCP, but utilizing the powerful foundation that Langbase workflows provide.

Langbase vs Langbase + AI Agent: Key Differences

Langbase Comparison Table

Integrating Runbear with Langbase transforms how teams access and operationalize their AI agents. Alone, Langbase is a developer-centric platform best suited for coding and backend orchestration; chat-based access and real-time team collaboration require custom work. With Runbear, teams experience a seamless, accessible layer: AI agents join their daily chat apps, workflows become instantly deployable, and multi-person collaboration emerges—without extra development. Scheduled automations, powerful internal search, and reporting features move from manual to automatic, freeing time and boosting

Implementation Considerations

Teams adopting a Langbase + Runbear workflow should consider a few key factors. First, initial setup requires connecting their Langbase agents to Runbear and verifying secure permissions for API access. Because Runbear works within your chat apps, employees may need lightweight onboarding to know how to invoke agents, schedule jobs, or retrieve data collaboratively. Organizations must assess if their Langbase agents are well-documented for a broader, non-technical audience, as Runbear shifts interaction from code to natural language. Change management is crucial: teams move from developer-centric ops to democratized, chat-driven access, which can increase both productivity and the importance of robust knowledge management. Finally, review cost and security—ensure Langbase configurations fit the usage scale, and restrict agent memory/actions as needed for data governance. When these factors are proactively managed, teams maximize ROI and adoption.

Get Started Today

The synergy of Langbase and Runbear marks a leap forward in AI agent-driven collaboration for modern teams. By making custom agents accessible where teamwork happens, organizations unlock daily, repeatable value—no matter their technical background. Whether you want smarter reporting, on-demand analytics, or scalable Q&A, this integration lets your AI agents become proactive team members. Start exploring Langbase + Runbear today to supercharge your workflows and empower your team’s intelligence at scale. Ready to bring AI agents into your team’s daily rhythm? Try the integration and reimagine what team productivity looks like—now powered by natural language and intelligent agents.