Pricing

Supercharge R&D technical support with AI and Ragie

Swiftask leverages your technical data indexed by Ragie to instantly answer complex R&D tickets.

Result:

Reduce the cognitive load on your engineers and accelerate technical incident resolution.

Managing R&D tickets is burning out your experts

R&D teams lose valuable time searching for information in scattered technical documentation. Each ticket requires lengthy manual investigation, distracting engineers from high-impact projects.

Main negative impacts:

Excessive search time: Engineers navigate through dozens of technical files to answer a single recurring question.
High resolution latency: The complexity of R&D topics extends response cycles, impacting internal stakeholder satisfaction.
Knowledge silos: Technical expertise is often centralized in a few individuals, creating critical bottlenecks.

By connecting Ragie to Swiftask, you create an intelligent interface that automatically queries your R&D knowledge bases to propose precise, context-aware answers.

BEFORE / AFTER

What changes with Swiftask

Traditional R&D support

A ticket arrives. The engineer must identify the correct technical document, browse it, verify the version, and write a reply. This process is manual, error-prone, and time-consuming.

R&D support with Swiftask + Ragie

The ticket is analyzed by the AI agent. Using Ragie, it instantly extracts relevant information from R&D documentation and generates a validated technical response, ready for support.

Implementing AI for your R&D in 4 steps

STEP 1 : Index your documents in Ragie

Centralize your specifications, manuals, and R&D reports in Ragie to create a searchable, vectorized knowledge base.

STEP 2 : Connect Ragie to Swiftask

Configure the integration in Swiftask to allow your AI agents real-time access to your Ragie database.

STEP 3 : Define support rules

Set the agent's behavior: tone, technical depth, and authorized sources for response generation.

STEP 4 : Deployment and learning

Activate the agent on your support channels. It learns from interactions to improve technical response accuracy.

Capabilities of your intelligent R&D agent

The agent analyzes ticket semantics to isolate the specific technical issue within your R&D documentation.

Target connector: The agent performs the right actions in ragie based on event context.
Automated actions: Extracting answers from technical PDFs, summarizing error reports, version comparison, and drafting recommendations based on documented best practices.
Native governance: Precision is ensured by Ragie's RAG (Retrieval-Augmented Generation) indexing, minimizing AI hallucinations.

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

Each Swiftask agent uses a dedicated identity (e.g. agent-ragie@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 for R&D

1. Accelerated resolution

Cut ticket processing time in half with instant access to information.

2. Easier onboarding

New hires access R&D knowledge via AI without constantly bothering seniors.

3. Technical consistency

Ensure uniform answers based on official and updated documentation.

4. Focus on innovation

Free up brainpower for your engineers by automating first-level support tasks.

5. Support scalability

Handle increasing ticket volumes without hiring additional technical staff.

Technical data security

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

Data isolation: Your documents in Ragie remain private and secure. The AI accesses them only through controlled requests.
R&D compliance: Full traceability of sources used by the AI for every generated response.
Granular control: Define which documents are accessible by which AI agent within your organization.
Robust infrastructure: Secure hosting compliant with industrial data protection standards.

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

RESULTS

Impact on R&D performance

Metric	Before	After
Doc search time	45 min/ticket	2 min/ticket
Tickets processed	10/day	40/day
Internal satisfaction	Moderate	Very high
Onboarding time	3 months	1 month

Take action with ragie

Reduce the cognitive load on your engineers and accelerate technical incident resolution.

Streamline your knowledge base management with Ragie

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