Swiftask indexes your Canvas documents to provide ultra-precise semantic search. Stop searching for keywords, start asking your data complex questions.
Result:
Save hours every week. Relevant information is extracted and summarized in an instant, regardless of document volume.
Document chaos: why standard search fails
In your Canvas workspaces, information is often scattered. Traditional keyword search returns dozens of irrelevant results or fails if the exact term isn't used. Your teams waste precious time digging through hundreds of pages manually.
Main negative impacts:
Swiftask connects your Canvas documents to a semantic search engine. The AI understands the meaning of your questions and extracts answers directly from your files, ensuring unmatched relevance.
BEFORE / AFTER
What changes with Swiftask
Standard keyword search
You're looking for specific information about an internal procedure. You type an approximate keyword, get 50 documents, open 5 of them, and end up asking a colleague because you didn't find the answer.
Semantic search with Swiftask
You ask your AI agent a natural question: 'What is the validation procedure for new projects?'. The agent analyzes your Canvas documents, understands the context, and answers you directly while citing sources.
Setting up your AI search engine in 4 steps
STEP 1 : Connect your Canvas space
Connect Swiftask to your Canvas documents in a few clicks. The AI immediately begins secure semantic indexing.
STEP 2 : Configure the search agent
Define search scopes and authorized sources. No technical skills are required to set up this agent.
STEP 3 : Semantic training
The agent automatically analyzes the structure and content of your Canvas files to understand relationships between business concepts.
STEP 4 : Query your data
Use the Swiftask chat to ask your questions. The AI scans your entire Canvas base to provide a synthesized answer.
Advanced search capabilities for Canvas
The agent evaluates semantic relevance, document update dates, and information hierarchy to prioritize the most accurate answers.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-canvas@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 adopt AI semantic search
1. Surgical precision
Stop wasting time filtering results. The AI understands the intent of your query.
2. Massive productivity gains
Drastic reduction in document search time for all your employees.
3. Access to tacit knowledge
Leverage your entire Canvas documentation, even what isn't explicitly named.
4. Trust in answers
Every answer is based on your actual documents with clear reference links.
5. Infinite scalability
Whether you have 10 or 10,000 documents, search speed and quality remain optimal.
Data security and privacy
Swiftask applies enterprise-grade security standards for your canvas automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your operational efficiency
| Metric | Before | After |
|---|---|---|
| Information search time | 10-20 minutes per query | Under 5 seconds |
| Relevance rate | Low (many false positives) | Very high (contextual answers) |
| Document access | Limited by file names | Based on semantic content |
| IT burden | Manual index maintenance | Automated and no-code |
Take action with canvas
Save hours every week. Relevant information is extracted and summarized in an instant, regardless of document volume.