Query your Cloudflare R2 files in natural language
Stop searching for files by name. Swiftask indexes the content of your Cloudflare R2 files to enable instant semantic search.
Result:
Access relevant information in seconds, regardless of the volume of stored data.
AI Agents
cloudflare r2
Connector cloudflare r2 · Secure OAuth 2.0
File name search is no longer enough
With terabytes of data in Cloudflare R2, finding specific information is a challenge. Traditional search methods fail against the complexity of unstructured content.
Main negative impacts:
Massive time loss
Your team members spend hours opening dozens of files to find specific data.
Siloed knowledge
Useful information is buried in your R2 archives, inaccessible to those who need it.
Operational inefficiency
The inability to quickly extract insights from documents slows down decision-making.
Swiftask turns your Cloudflare R2 files into a living knowledge base. With AI, you ask complex questions and get answers based on the actual content of your documents.
BEFORE / AFTER
What changes with Swiftask
Classic search
You're looking for a specific contract. You try several keywords in the file name. You end up browsing folders and opening files one by one.
Swiftask semantic search
You ask your AI agent: 'What are the termination clauses in contract X?'. The agent analyzes the documents in R2 and gives you the exact answer instantly.
Setting up your R2 indexing in 4 steps
1
STEP 1 : Connect your Cloudflare R2 bucket
Configure access to your R2 bucket in Swiftask. The connection is secured via dedicated API keys.
2
STEP 2 : Enable intelligent indexing
Swiftask automatically scans and vectorizes your files (PDF, docx, txt, etc.) to make them intelligible to the AI.
3
STEP 3 : Create your search agent
Configure a specialized agent capable of querying this indexed database with your own criteria.
4
STEP 4 : Query your data
Ask your questions via the Swiftask interface or via API. The agent extracts relevant answers from the R2 files.
Advanced search capabilities
The AI understands the intent behind your question and analyzes the semantic relevance of documents rather than just matching keywords.
- Target connector: The agent performs the right actions in cloudflare r2 based on event context.
- Automated actions: Multi-format file support. Cross-document search. Source citations for verification. Automatic index updates when adding new files.
- Native governance: Your data stays in your ecosystem. Swiftask ensures total confidentiality during the indexing process.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-cloudflare-r2@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why choose semantic search
Immediate productivity gains
Drastically reduce information search time for your teams.
Accurate answers
Get contextual answers based on your own internal documents.
Unlimited scalability
Whether you have 100 or 1,000,000 files, search performance remains constant.
Use natural language
No need to know folder structures or naming conventions.
Unlock data value
Breathe new life into your dormant archives on Cloudflare R2.
Security and privacy
Swiftask applies enterprise-grade security standards for your cloudflare r2 automations.
- Data encryption: Your files are treated with the highest security standards during indexing.
- Access control: You manage who can query which R2 buckets via Swiftask.
- Compliance: Solution designed to meet enterprise data governance requirements.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your operations
| Metric | Before | After |
|---|---|---|
| Search time | 10-30 minutes | Less than 5 seconds |
| Success rate | Variable (human) | Constant (AI) |
| Data volume | Limited by manual indexing | Unlimited (R2) |
Take action with cloudflare r2
Access relevant information in seconds, regardless of the volume of stored data.