Blog
Use Beeuni for everyday paperwork, web research, AI dataset preparation, and building agent features into your product.
Infrastructure for RSI research: running and evaluating self-improving agents
How Beeuni helps researchers run repeated agent-improvement experiments: edit code and instructions, execute tests, investigate failures, and compare versions.
Use Beeuni to run and evaluate a model fine-tuning experiment
Have an agent prepare training data, run a fine-tuning job on your connected training computer, inspect failures, and compare model outputs.
Research prospective SaaS customers before writing the outreach
Build a prospect shortlist with evidence of fit, current needs, and unanswered questions using Beeuni’s browser and your connected CRM.
Keep track of SaaS competitor pricing and product changes
Use Beeuni to check competitor websites, compare pricing terms, and turn product changes into a brief your small SaaS team can act on.
Build an AI training dataset from your existing documents
Collect approved support tickets or documents, then prepare a reviewable JSONL dataset with source references, duplicate checks, and separate evaluation splits.
Preparing documents for RAG: fix the source before changing the prompt
Collect documents from a connected knowledge base or public help site, then check extraction, versions, and chunk boundaries before indexing them for RAG.
Write release notes from pull requests without publishing internal noise
Have Beeuni read a connected GitHub repository, check the release range, and draft user-facing notes with references to the changes.
Use Beeuni as the agent backend for your product
Connect your product to an agent that browses supplier sites, reads authorized sources, runs comparisons, and returns results through the Beeuni SDK.
Test a website with an AI agent and get reproducible bug reports
Give an agent a website test plan, record expected and actual behavior, and turn failed checks into bug reports another developer can reproduce.
Group user feedback without losing the original requests
Read feedback from connected support and project tools, group related reports, and prepare issue drafts that retain the original conversations.
From tool calls to an agent computer: how the architecture changes
Follow an agent from a tool-calling loop to a computer that runs real tasks, with separate environments, saved state, permissions, and inspectable progress.
Turn meeting notes into decisions and action items
Read meeting notes through connected apps, check decisions against the transcript, and prepare follow-up tasks with source references.
Moving house: reconcile bookings, emails, and deadlines
Use connected email, documents, and calendar bookings to find moving deadlines, catch conflicting appointments, and prepare the messages that resolve them.
How to compare home service quotes before hiring
Compare contractor quotes by scope, materials, exclusions, payment terms, and total cost before choosing a home service provider.
Compare travel options from live websites
Build a travel shortlist with comparable prices, baggage rules, cancellation terms, source links, and the time each offer was checked.
Clean a messy CSV without losing rows
A practical CSV cleanup checklist for dates, identifiers, duplicates, missing values, and row-by-row reconciliation.
Beeuni, E2B, and Daytona: choosing infrastructure for your agent product
Compare sandbox infrastructure with Beeuni’s computer for agents: ready-to-use tools, code execution, environment control, and multi-step agent work.
Beeuni vs. Manus and Muse: agent infrastructure and agent applications
Beeuni provides computer infrastructure for agents. Manus and Muse focus on applications people use to complete tasks. Compare their audiences, execution environments, and integration into your own product.
What is an AI computer? Traditional PCs and computers for agents
How a computer changes when agents operate its software: from traditional PC interaction to tool execution, browser feedback, processes, files, and session state.