Pricing

Analyze market history with StockNewsAPI and AI

Swiftask connects your AI agents to StockNewsAPI archives. Query years of financial news to detect patterns and validate your investment theses.

Result:

Go beyond the immediate. Master historical context for informed decision-making.

The challenge of leveraging financial archives

Extracting insights from thousands of past financial news articles is a massive task. Without the right tool, data remains locked in raw databases, unusable for quick decision-making.

Main negative impacts:

Loss of strategic context: Ignoring past events impacts understanding of current market cycles.
Complex extraction: Manual processing of massive archive volumes is inefficient and error-prone.
Decision latency: Time spent searching prevents agile reactions to market changes.

Swiftask automates StockNewsAPI querying. Your AI agent instantly traverses history to synthesize past trends according to your criteria.

BEFORE / AFTER

What changes with Swiftask

Manual search

You browse news aggregators, filter by dates, read dozens of articles, and try to manually correlate these events with price variations.

Swiftask AI search

You ask your Swiftask agent: 'Analyze the impact of Fed announcements on stock X during Q3 2023'. The agent queries StockNewsAPI, synthesizes data, and delivers the report.

Unlock your archives in 4 steps

STEP 1 : Connector configuration

Integrate your StockNewsAPI key into Swiftask in a few clicks.

STEP 2 : Agent definition

Set up an AI agent specialized in analyzing historical financial data.

STEP 3 : Natural language queries

Ask complex questions about specific timeframes or stock themes.

STEP 4 : Analysis and synthesis

Retrieve structured reports based on real data provided by the API.

Advanced search capabilities

The agent crosses dates, stock tickers, and sentiments expressed in archives to provide a comprehensive view.

Target connector: The agent performs the right actions in stocknewsapi based on event context.
Automated actions: Date range search, sector filtering, historical sentiment analysis, key fact extraction, event-data correlation.
Native governance: Swiftask ensures every analysis is sourced directly from StockNewsAPI data.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-stocknewsapi@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.

Benefits for your analysis

1. Massive time savings

Analyze years of data in seconds.

2. Increased precision

Reduced cognitive biases linked to selective reading.

3. Search history

Keep a record of your analyses for internal audits.

4. Intuitive interface

Natural language replaces complex API queries.

5. Competitive intelligence

Better understand your competitors' past moves.

Data security

Swiftask applies enterprise-grade security standards for your stocknewsapi automations.

Key encryption: Your API access is stored securely.
Confidentiality: Your searches and analyses remain private within your instance.
Compliance: Adherence to security standards for financial data.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your productivity

Metric	Before	After
Search time	Several hours	A few minutes
Data volume analyzed	Limited by human reading	Thousands of articles simultaneously
Insight quality	Subjective	Based on exhaustive data

Take action with stocknewsapi

Go beyond the immediate. Master historical context for informed decision-making.