Narada
Agentic process-automation and computer-use platform built on Large Action Models.
Narada is an agentic process automation platform built on Large Action Models, from a team with roots in UC Berkeley and Stanford AI research. Its agents take natural language or voice instructions and carry them out across web apps, desktop apps and Citrix through a Chrome extension or serverless cloud browser sessions, mixing interface automation with API calls.
Builders work in Agent Studio, a visual workflow editor that chains navigation, clicks, extraction, loops and conditions with LLM driven agent steps and deterministic Python steps, or write Python agents with the SDK. Agent Maker and Imitation Learning generate agents from a description or a demonstration. Agents can call custom tools defined with MCP Builder, connect Gmail, Calendar, Slack and Zoom through plugins, and retrieve from Vector Stores of the customer's own documents. Approval steps pause an agent before it sends, submits, buys or deletes, and action traces with GIF recordings show what each run did.
Outside systems drive Narada through a REST API, the Python SDK, an A2A agent card and MCP. SOC 2 Type 2 and a HIPAA option are stated, and on premises deployment is offered on the Enterprise plan. Narada does not document roles or SSO, a choice of model, or schedules for the customer's own agents.
Vendor details
Canonical URL
https://narada.ai
Category
Browser / computer-use agent
Company status
independent
Use cases & customers
In practice
The tool you need to automate has no usable API. Narada drives it through browser-based UI automation alongside API calls, so it can run applications that integration platforms simply can't reach.
Filing an expense report means clicking through Concur, updating records, and chasing approvals. You tell Narada in plain language and it plans and executes the multi-step task across those siloed tools.
Automations break the moment a vendor changes a screen. Narada adapts and self-heals as tool interfaces change, instead of failing silently until someone notices.
Sources & related URLs
Research sources
Agentic Index coverage score
10.5 / 14 capabilities · 75%
| Integrations & Tool Calling | Full |
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Plugins connect Gmail, Calendar, Slack, Zoom and more, MCP Builder defines custom tools agents can call, and Python agents call APIs directly, beside interface automation of enterprise apps. The plugin list covers Zoom meetings and invites, Gmail, Google Calendar and Drive, Slack search across several workspaces, HubSpot contacts, deals and timelines, Salesforce contacts, leads and opportunities with call logs added, and web search with citations, each switched on in the Plugins sidebar and signed in to its own account. The SDK also reads and writes Google Sheets. SourceNarada, docs.narada.ai Plugins, MCP Builder and API referenceread 2026-10-05 |
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| Workflow Orchestration | Full |
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Agent Studio's visual workflow editor chains navigation, clicks, extraction, loops and conditions with LLM driven agent steps and deterministic Python code steps, Python agents give full programmatic control, and tasks run in parallel across browser windows. Input variables feed values into a workflow when it runs, and structured output returns results in a shape the caller defines. SourceNarada, docs.narada.ai Agent Studio, Parallel Execution, Input Variables and Structured Outputread 2026-10-05 |
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| Knowledge Grounding & RAG | Full |
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Vector Stores hold the customer's uploaded documents, PDFs and text files, are connected to agents and searched semantically at run time, and grow as new files are uploaded. Files can also be attached to a single task through the API, and an agent can read the page in front of it as simplified HTML, full HTML or a screenshot. SourceNarada, docs.narada.ai Vector Stores and API referenceread 2026-10-05 |
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| Human Oversight & Guardrails | Full |
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A user_approval step pauses an agent and shows an approve or reject card before it sends an email, submits a form, approves a purchase or takes a destructive action, and prompt_for_user_input collects values before it continues. The Slack plugin drafts messages for the user to review before they are sent. SourceNarada, docs.narada.ai Human-in-the-Loop Steps and Pluginsread 2026-10-05 |
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| Security, Identity & Governance | Partial |
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SOC 2 Type 2, a HIPAA option and a statement that customer data does not train models are on the homepage, with BAA and DPA on Enterprise; access is by API key and agents can be shared with a team, but no roles, SSO or SCIM are documented. The homepage also lists GDPR and CCPA compliance and CASA Tier 2 certification, and the docs cover account deletion. SourceNarada, narada.ai and docs.narada.ai Authentication and Account Deletionread 2026-10-05 |
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| Observability & Auditability | Full |
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Action traces return step by step logs of each automation in the API response, with a visual GIF recording of the run. Screenshots can be taken at any step, downloaded files are captured, and a task's result can be fetched by polling or pushed to a webhook. SourceNarada, docs.narada.ai Action Trace, Screenshots, File Downloads, Polling and Webhooksread 2026-10-05 |
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| Memory & State Persistence | Partial |
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Custom Instructions are a store of preferences the user maintains, and Narada applies them to all future actions. Narada describes no memory that the agent writes for itself. An interrupted cloud browser session can be picked up again with its saved session and window IDs. SourceNarada, docs.narada.ai Custom Instructions and Cloud Browser Sessionsread 2026-10-05 |
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| Deployment & Data Residency | Full |
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On premises deployment is offered on the Enterprise plan and the homepage describes on prem options for data privacy, including Citrix and on premises claims processing, beside the cloud service and cloud browser sessions. Cloud browser sessions are serverless and need no local Chrome, several can run in parallel, and each keeps accruing cost until it is closed or times out. Proxy settings for the agent's browsing are documented. SourceNarada, narada.ai and docs.narada.ai Cloud Browser Sessions and Proxy Settingsread 2026-10-05 |
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| Prebuilt Agents, Templates & Packs | Partial |
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Agent Maker and Imitation Learning generate agents from a description or a demonstration, the Prompt Library saves the user's own prompts, and a few built in jobs ship ready (Morning Brief emails, Document Analyzer). Narada publishes no catalog of packaged agents or templates. It is built for jobs such as order and invoice processing, pricing research, claims processing, CRM updates, accounts receivable, travel and expense processing and HR requests. SourceNarada, narada.ai and docs.narada.ai Agent Makerread 2026-10-05 |
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| Triggers & Channel Coverage | Partial |
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Tasks start from the Chrome extension chat, voice messages, the Python SDK, the Remote Dispatch REST API, A2A and MCP, with results pushed by outbound webhook; the only scheduled run documented is the fixed 5 AM Morning Brief email, and no schedule or event trigger for the customer's own agents is documented. A Remote Dispatch call can send a task to the user's Chrome extension or to a cloud browser session. SourceNarada, docs.narada.ai Remote Dispatch and Cloud Browser Sessionsread 2026-10-05 |
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| Model Flexibility & Routing | Not documented |
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Narada runs its own Large Action Models, and the docs offer no choice of model or provider for agent steps. The homepage presents these Large Action Models as the core of the product and states that customer data is not used to train them. SourceNarada, narada.ai and docs.narada.ai Agent Studioread 2026-10-05 |
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| APIs, SDKs & MCP Extensibility | Full |
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A Python SDK, a Remote Dispatch REST API with documented request and response, and an A2A agent card at https://api.narada.ai/fast/v2/a2a/.well-known/agent.json with its authentication, plus MCP over Streamable HTTP, let outside callers drive Narada. The SDK reference covers calls such as run, agentic_selector, agentic_mouse_action, get_screenshot, go_to_url, read_google_sheet and write_google_sheet, and a Cursor integration is documented. SourceNarada, docs.narada.ai A2A and MCP, API reference and Cursor Integrationread 2026-10-05 |
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| Testing, Debugging & Optimization | Partial |
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Typed errors such as timeouts are raised for the customer's code to handle, and traces show what a run did. Narada publishes no way to test agents on sample tasks, score the results or hold back a release that falls short. Structured output lets the calling code check the shape of an agent's result before using it. SourceNarada, docs.narada.ai Error Handling and Structured Outputread 2026-10-05 |
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| Browser & Computer Use | Full |
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Narada's agents drive the browser through its Chrome extension or serverless Cloud Browser Sessions, with remote browser control and mouse and selector actions in the SDK, and the homepage describes automating desktop apps, web and Citrix. Applications it names include ServiceNow, SAP, Salesforce, Workday and SAP Concur, and the automations are described as adapting when a screen changes. SourceNarada, narada.ai and docs.narada.ai Cloud Browser Sessionsread 2026-10-05 |
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The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Pricing
Free tier; Enterprise by quote
Included quota
Free: 400 Narada Credits and limited API access. Enterprise (custom): custom credits, API access, priority support, on premises deployment, BAA, DPA, GDPR and HIPAA terms, contract redlining, a dedicated TAM and use case tuning.
What is public
narada.ai/pricing publishes a free tier (400 Narada Credits, limited API access) and a quoted Enterprise plan; no paid self serve plan or credit price is published.
Free / trial
Free tier: 400 Narada Credits, limited API access
Key ambiguities
How many credits a task consumes and what a credit costs are not published.
Missing data
The price of credits and of the Enterprise plan.
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Alternatives to Narada
The closest documented capability profiles to Narada among browser and computer-use agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Automat AI11.5 / 14Adds documented Model Flexibility & Routing
- H Platform9.0 / 14Fuller documented coverage on Triggers & Channel Coverage
- Browser Use11.5 / 14Adds documented Model Flexibility & Routing
- Skyvern11.5 / 14Adds documented Model Flexibility & Routing
- Autotab8.0 / 14Fuller documented coverage on Triggers & Channel Coverage
- Fellou8.0 / 14Fuller documented coverage on Triggers & Channel Coverage
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded