Analyze your TimescaleDB data by simply asking questions
Swiftask allows your teams to query your TimescaleDB databases using natural language. Get complex insights without writing a single line of SQL.
Result:
Democratize access to time-series data and accelerate strategic decision-making.
AI Agents
timescaledb
Connector timescaledb · Secure OAuth 2.0
The SQL query bottleneck
To extract insights from your time-series data, you currently depend on data engineers. Every business question requires a SQL query, creating frustrating delays and constant technical dependency.
Main negative impacts:
Critical analysis delays
Data-driven decisions are slowed down by the availability of SQL experts to write queries.
Technical team overload
Your engineers spend their time running ad-hoc queries instead of focusing on data architecture.
BI adoption barrier
Business decision-makers cannot explore data independently, limiting the scope of analysis.
Swiftask acts as an intelligent abstraction layer. Your AI agent translates your business questions into SQL queries optimized for TimescaleDB, ensuring precise answers in seconds.
BEFORE / AFTER
What changes with Swiftask
The traditional cycle
A business analyst has a question about a time trend. They send a ticket to the data team. The engineer writes the SQL, validates the results, and sends a CSV. This process takes hours or days.
The Swiftask approach
The analyst asks their question directly to the Swiftask agent: 'What is the average consumption per sensor over the last 30 days?'. The agent generates and executes the SQL, and displays the results instantly.
Setting up your data assistant in 4 steps
1
STEP 1 : Connect your TimescaleDB instance
Configure secure access to your TimescaleDB database in Swiftask via an encrypted connection.
2
STEP 2 : Define schema context
Give your agent an overview of tables and relationships so it understands your time-series data structure.
3
STEP 3 : Configure access rules
Restrict queries to necessary tables to ensure security and performance of your database.
4
STEP 4 : Query in natural language
Ask your questions. The agent generates the SQL, verifies it, and returns actionable data.
Intelligent SQL agent capabilities
The agent understands time-series data specifics (rolling windows, time aggregates, chronological series).
- Target connector: The agent performs the right actions in timescaledb based on event context.
- Automated actions: Complex SQL query generation, series aggregation, advanced time filtering, trend visualization, data export.
- Native governance: All generated queries are audited to ensure performance and security.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-timescaledb@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.
Operational benefits
Business team autonomy
No more SQL skills needed to get immediate answers.
Reduced Time-to-Insight
Go from question to answer in seconds, not days.
Optimized resource allocation
Free your data engineers from repetitive reporting tasks.
Unlimited exploration
Ask as many questions as needed to refine your understanding of the data.
Enhanced security
Strict data access control at the agent level.
Data security
Swiftask applies enterprise-grade security standards for your timescaledb automations.
- Encrypted connection: Secure TLS connection between Swiftask and your TimescaleDB instance.
- Read-only access: The agent is configured by default as read-only to protect your data integrity.
- Full audit: Every question asked and every SQL query generated is logged.
- Compliance: Adherence to enterprise data security standards.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on productivity
| Metric | Before | After |
|---|---|---|
| Question response time | Several hours | Under 5 seconds |
| Ad-hoc queries handled | Total IT dependency | Full business autonomy |
| Analysis precision | Manual error risk | AI-optimized SQL generation |
Take action with timescaledb
Democratize access to time-series data and accelerate strategic decision-making.