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Support Custom Endpoint when Adding Models
Add optional support to add custom API base URL when adding new model credentials so that customer can choose what region / instance they want to connect to
Add AI Decision Node
Add a node that uses decision models such as OpenAI’s Decisions API and Jev to choose from builder-defined outcomes and route the workflow accordingly. Builders configure the question, input context, provider, and allowed branches. The node returns a structured choice; invalid results or provider errors go to a fallback branch. This removes the need to prompt a general-purpose LLM and parse its text just to make a routing decision.
Extend Request Metadata to support session info
Extend request metadata with optional fields for session enrichment: userId, sessionId, and orgId Location and client context: IP address, coordinates, country, city, device, and browser Automatically capture available fields for requests made through widgets and client-side SDKs. Allow developers to supply or override supported fields when needed. Make each field filterable in logs and reports so teams can investigate requests by user, session, organization, or client context. Acceptance criteria Requests can store the optional user, session, organization, and location/client fields. Widgets and client-side SDKs populate available fields automatically. Logs and reports support filtering by each field. Missing fields do not block requests.
Fetch user's data using project ids
Feature - Get the user’s data using project ids Why - This will help in identifying the users that are affected during the potential outage
Bulk Retry for Failed Flows
Problem: After an incident, multiple flows may fail due to the same underlying issue. Currently, we have to retry each failed flow individually from Studio, which is time-consuming and inefficient when there are a large number of failures. Request: Add a Bulk Retry functionality in Studio that allows users to select multiple failed flow executions and retry them together in a single action. Expected Benefit: This would significantly reduce manual effort and make incident recovery faster, especially when a large number of flows are affected by the same incident.
API based functionality to execute containers
One of our customers is currently using our Enterprise API to manage their workflows programmatically, including creating workflows, triggering executions, and performing other workflow-related actions through the API. However, there is currently a limitation with the Enterprise API: there is no functionality available to execute a workflow directly inside a container through a triggering API request. While customers can trigger and manage workflows using the existing API, they cannot specify or initiate the execution of a workflow within a containerized environment through the API. https://lamatic.notion.site/Lamatic-Enterprise-API-1a02e0e26128801ba14cc8184926b78d
Option to Enable or Disable Auto-Format in IDE
Feature - When nodes are added or removed in the flow UI, the layout automatically re-formats. Why - This causes unexpected changes in the flow's appearance, leading to a frustrating user experience. Where would it help most - This feature gives users control over the flow formatting behavior, improving usability and reducing frustration. Extras - Introduce a toggle switch that allows users to choose whether they want auto-formatting enabled or disabled. Auto-format ON: The flow automatically adjusts layout when nodes change. Auto-format OFF: The flow layout remains unchanged, preserving the user’s manual arrangement even when nodes are added or removed. Sample format Image before adding END Node Format image after adding END Node
Enhance Flow Comparison
Multi-tab Support and Flow Comparison Enable right-click to open flows in new tabs for easy comparison Support multiple tabs within the main window (similar to how Linear handles native apps) Display full flow names - currently get cut off/truncated in the UI, making it difficult to distinguish between flows Allow side-by-side visual comparison of different flow versions Consider implementing an Electron wrapper for native app experience with better tab support Cross-Environment Flow Navigation Ability to change environments within a single flow view - users want to see what the same flow looks like in staging while viewing production Maintain flow state when switching environments instead of returning to flow home screen Use flow slug associations to link flows across environments (dev/staging/production) Reduce manual effort required to promote workflows from dev → staging → production
Support variables in zod schema of generate json node
There should be option to add zod schema as a variable in generate json node
Support for Local Development
An open-source SDK to address developer adoption barriers and vendor lock-in concerns that are currently limiting growth. Problem Developers resist Lamatic's no-code/low-code platform due to limited library support, lack of local development capabilities, missing CLI tools, and weak version control integration Enterprise and startup customers worry about vendor lock-in and business continuity if Lamatic changes pricing or discontinues service Competitors offering open-source alternatives have an advantage Proposed Solution Build a standalone, open-source SDK enabling developers to: Develop AI agents/systems locally in their preferred IDE Test and debug offline without cloud dependency Use Git for version control across all project components Create custom integrations and capabilities Deploy anywhere (on-premise, private/public cloud, or Lamatic-managed) Compile flows into executable code via CI/CD pipelines Core Architecture YAML-based configuration system with: Pre-built node libraries for AI components Containerized runtime (Pod + Core) executing configurations Compiler for optimizing YAML into executable workers Local web editor accessible via localhost CLI for all development operations Multiple invocation methods (API, webhooks, widgets)
Support For dynamic File References in Flow Config
The nodes are embedded inline with formatting artifacts (hello\\nhello), apparent test content, and no versioning metadata. Editing it requires understanding the entire config file, and changes produce noisy diffs that obscure actual prompt improvements. Before: prompts: - id: 187c2f4b-c23d-4545-abef-73dc897d6b7b role: assistant content: >- hello hello Important:please provide the response in wrap text format... After: prompts: - id: rag_system_prompt_v1 role: assistant # Edit prompts in /prompts/rag_system.md — supports preview & versioning contentRef: ./prompts/rag_system.md version: "1.2.0" lastUpdated: "2025-01-15" Developer Impact: Prompts become first-class artifacts — reviewable in PRs, A/B testable, and editable without touching pipeline config.
Flow Control Enhancements
Maximum zoom in level controls - prevent excessive zooming that makes interface unusable Maintain consistent zoom levels with horizontal scroll when flows extend beyond screen width Reset zoom level functionality with percentage display Boundary controls for zoom out levels to maintain readability
Show indication on Nodes when logic is applied
When there is logic on a node and it is like retry or any logic, I think the node should have an indicator that there is logic applied. Whether that's the little retry logo, the little blue square, whatever it might be, because when you've got forty nodes on a canvas and maybe ten of those are LLM nodes that you want to put retry logic on, you can't retain the knowledge and understanding if you put it to all of them. You have to keep checking them all over again. It would be great if I could see exactly which ones I've already applied the logic to.
Prompt Snippet
Ability to Create Prompt Snipped Library Which could be synced across various AI nodes
Log User Meta in API requests
Ability to college following user meta [ UserID, SessionID, OrgID ] in API request and pass it to - Logs - Reports - External telemetry - Langfuse
Manual Test Case for Nodes
Give option to pass custom input to a node on Testing to individually pass a particular test case instead of executing the whole flow
Show Testing Meta Data should show some more details
Show Testing Meta Data should show some more details • show timings and latency • Parallel execution doesn't show accurate timings instead mimic the timings from a sequential execution
Include Flow Metadata in version controls
Extend git integration to include flow metadata like tags and owners, ensuring complete version control for all flow components.
Modified Node Visual Indicators
Add visual indicators (similar to VS Code's file change indicators) to show which nodes have been modified but not yet saved, helping users track changes before deployment.