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.
AI Agents
ragie
Connector ragie · Secure OAuth 2.0
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
1
STEP 1 : Index your documents in Ragie
Centralize your specifications, manuals, and R&D reports in Ragie to create a searchable, vectorized knowledge base.
2
STEP 2 : Connect Ragie to Swiftask
Configure the integration in Swiftask to allow your AI agents real-time access to your Ragie database.
3
STEP 3 : Define support rules
Set the agent's behavior: tone, technical depth, and authorized sources for response generation.
4
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
Accelerated resolution
Cut ticket processing time in half with instant access to information.
Easier onboarding
New hires access R&D knowledge via AI without constantly bothering seniors.
Technical consistency
Ensure uniform answers based on official and updated documentation.
Focus on innovation
Free up brainpower for your engineers by automating first-level support tasks.
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.