Stop searching by keywords, start searching by meaning. Swiftask connects your BigBox instance to an AI capable of understanding your documents and answering your questions precisely.
Result:
Save hours every week by accessing exact information instantly, even when buried in thousands of files.
Traditional keyword search is failing you
Within BigBox, finding specific information becomes a challenge as data volume grows. Keyword search either returns too many irrelevant results or nothing at all if the exact term isn't used. This inefficiency brings decision-making to a halt.
Main negative impacts:
Swiftask adds a layer of semantic AI on top of BigBox. It analyzes the context of your documents and your queries to understand the intent behind the search.
BEFORE / AFTER
What changes with Swiftask
Classic search in BigBox
You type 'supplier contract'. You get 500 results. You have to open each file manually to check if it's the current contract, the right supplier, or the correct clause.
Semantic search with Swiftask
You ask: 'What is the renewal amount for supplier X's contract for 2024?'. Swiftask analyzes the documents in BigBox and gives you the exact answer, with sources, in seconds.
Activating your AI search engine in 4 phases
STEP 1 : Secure BigBox connection
Pair your BigBox instance with Swiftask through a secure integration that respects your existing access permissions.
STEP 2 : Intelligent content indexing
Swiftask processes your BigBox data to create semantic representations (embeddings) of your documents, without moving your files.
STEP 3 : Search agent configuration
Define the search scope for your agent and response instructions to tailor the tone and precision.
STEP 4 : Natural language interrogation
Ask your questions to the Swiftask agent. It scans the BigBox content and synthesizes relevant answers.
Advanced search capabilities
The agent evaluates semantic relevance, temporal context, relationships between entities, and source reliability within your BigBox.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-bigbox@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 semantic search
1. Surgical precision
Get direct answers instead of a list of potential links.
2. Contextual understanding
The AI understands synonyms, related concepts, and the intent behind your query.
3. Massive productivity boost
Drastically reduce the time spent navigating file trees.
4. Zero data movement
Your files stay in BigBox; Swiftask only indexes the content for search.
5. Immediate adoption
Query your knowledge base using natural language, as if you were talking to an expert.
Security and data privacy
Swiftask applies enterprise-grade security standards for your bigbox 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 |
|---|---|---|
| Average search time | 10-15 minutes | Under 30 seconds |
| Relevance rate | Low (noisy results) | Very high (targeted answers) |
| Data coverage | Limited to file names | 100% of textual content |
| Business accessibility | Technical expert required | Natural language usage |
Take action with bigbox
Save hours every week by accessing exact information instantly, even when buried in thousands of files.