Natural language agent creation
Create AI agents from natural language rather than only from low-level configuration, positioning the product around prompt-led agent building.
Okibi
RevendiquerOkibi is a natural language platform for creating AI agents. Build task-specific agents in minutes with templates for customer research, Twitter posting, Google Sheets and PostHog analysis.
Overview
Okibi is a natural language platform for creating AI agents. The homepage positions it as a way to build agents in minutes, with a template gallery that shows example agents for customer research, Twitter posting, Google Sheets assistance, and PostHog analysis.
The site also exposes standard account access flows for sign-in and sign-up, suggesting a product that users access through a web app. Beyond the public landing pages, the collected source does not provide detailed documentation on setup, integrations, pricing, or deployment options.
Core capabilities
Template gallery
Browse ready-made examples for common workflows, including customer research, social content generation, spreadsheet assistance, and event analysis.
Multiple authentication options
Start an account or sign back in with GitHub, Google, or email link authentication.
Task-specific agent templates
Build agents around specific tasks shown in the gallery, such as identifying prospects with Clearbit or analyzing PostHog events.
Custom agent request flow
Request a custom agent from the homepage when a template does not match the intended workflow.
Practical uses
Customer prospect research
A product or growth team can use the customer research template to identify potential prospects for a product, with Clearbit mentioned as part of the example workflow.
Social video publishing
A content or social team can use a Veo3-based template to generate videos and post them to Twitter as part of a repeatable publishing flow.
Spreadsheet assistance
An operations or analytics user can rely on a Google Sheets agent to help manage spreadsheet work with AI assistance.
Event analysis
A product analytics team can use the PostHog analysis template to fetch and review event data without building a custom analysis tool from scratch.
Pros and Cons
Pros
- Positions agent creation around natural language input.
- Provides concrete template examples for several common workflows.
- Supports common sign-in methods through GitHub, Google, and email link.
- Offers a path to request a custom agent when templates are not enough.
Cons
- The collected source does not show detailed pricing or plan information.
- Integration coverage is only partially visible through template examples, not through a documented integrations list.
- The public pages do not explain the full agent-building workflow in detail.
FAQ
What is Okibi used for?
Okibi is presented as a natural language platform for creating AI agents. The site also shows template examples for customer research, generating and posting videos to Twitter, managing Google Sheets, and analyzing PostHog events.
How do users get started?
The public pages shown here demonstrate sign-in and sign-up flows with GitHub, Google, and email link options, but they do not document the full setup process or creation workflow.
What does Okibi cost?
The source text does not list pricing details, billing models, or plan limits. It only shows that a pricing page exists.
Which integrations are supported?
The collected pages do not provide documented integrations or technical limits. Template examples mention Clearbit, Veo3, Google Sheets, and PostHog, but no broader integration list is shown.
Quick Facts
- Category
- AI Agents
- Platform
- Web app
- Primary use
- Create and run AI agents from natural language
- Authentication
- GitHub, Google, email link
- Source domain
- okibi.ai