Stop wasting time searching. Swiftask understands the meaning behind your queries to extract relevant data from your Mitra databases instantly.
Result:
Gain precision and accelerate decision-making by accessing the right information in record time.
AI Agents
mitra
Connector mitra · Secure OAuth 2.0
Traditional search engines rely on exact term matching. If you don't use the exact word, the information remains invisible. In large Mitra datasets, this leads to significant productivity losses.
Main negative impacts:
Irrelevant results
Keyword-based searches often return too many or off-topic results, cluttering your workflow.
Information silos
The inability to semantically link documents prevents discovering critical relationships between your data.
Operational time loss
Staff spend hours refining queries instead of processing useful information.
Swiftask's semantic search understands the intent behind your question. It explores your Mitra data in depth to provide contextual answers, not just a list of files.
BEFORE / AFTER
Traditional search in Mitra
You look for a specific report. You type a keyword. You get 50 documents, none are the right one. You have to open each file manually to check its content.
Semantic search with Swiftask
You ask a complex question in natural language. Swiftask analyzes your Mitra data and delivers directly the relevant paragraph or summary you expected.
1
STEP 1 : Connect your Mitra data
Enable the Mitra connector in Swiftask to securely index your documents and knowledge bases.
2
STEP 2 : Configure indexing
Define the data scopes your agent should analyze to optimize result relevance.
3
STEP 3 : Train your agent
The Swiftask AI learns the structure and business context of your documents to improve semantic understanding.
4
STEP 4 : Natural language querying
Ask your questions via the Swiftask interface and get answers based on the real content of your data.
Swiftask uses advanced language models to turn text into semantic vectors, allowing it to capture nuances and synonyms.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-mitra@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.
Get exact answers through understanding business context.
Eliminate the phase of reading irrelevant documents to find information.
Make your Mitra databases usable by everyone, without technical expertise.
Allow your teams to focus on analysis rather than searching.
Semantic search respects the access permissions defined in Mitra.
Swiftask applies enterprise-grade security standards for your mitra automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
| Metric | Before | After |
|---|---|---|
| Average search time | 10-15 minutes | A few seconds |
| Relevance rate | Low (keyword-based) | Very high (semantic) |
| Volume of analyzed data | Limited by human memory | All indexed databases |
| Setup time | Heavy IT project | Activation in a few clicks |
Gain precision and accelerate decision-making by accessing the right information in record time.