Salesforce Healthcare Germany

deinePflege

Customer Service Automation

deinePflege's medically trained support staff was spending too much time on routine care-box and application questions, even as paper-heavy healthcare workflows and rising demand made 24/7 service impossible to staff economically.

$300,000 annually
10,000 bills each month
24/7 customer support
40% of support cases in seconds

Reported impact

Business outcome

deinePflege expects faster access to care support, lower case-handling costs, and more staff time for counseling and medically complex work instead of repetitive case administration.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

deinePflege is using Agentforce to convert repetitive care-support work into authenticated, around-the-clock digital service. Customer cases, contact history, and operational content live in Service Cloud and Data Cloud, letting Agentforce verify eligibility, answer questions about in-home care, and guide customers through next steps in seconds instead of forcing medically trained reps to complete each workflow by hand. When a request crosses into sensitive territory, the agent hands the interaction to a human rep together with the full conversation context so customers do not repeat themselves. The same design is being extended to WhatsApp, email, and voice, while the Einstein Trust Layer and strict authentication protect regulated health information. Agent Builder gives the team a low-code way to refine actions, helping deinePflege scale service without rebuilding its support architecture.

Data flow

Email and phone requests enter Service Cloud, where Agentforce combines contact history with FAQ, document, and offering data from Data Cloud. Authenticated answers are delivered immediately, sensitive cases are handed to reps with context, and the same model is being extended to WhatsApp, email, and voice channels.

Solution architecture

5 components · 5 layers
  1. Compute
    • Agentforce Handles common support conversations and guides customers through approved next steps.
  2. Storage
    • Data Cloud Holds FAQs, documents, and care-offering data that the agent reasons across.
  3. Serving
    • Service Cloud Stores contact history and service context used during support interactions.
  4. Orchestration
    • Agent Builder Lets the team configure and refine support agents with low-code tools.
  5. Governance
    • Einstein Trust Layer Protects regulated customer data with masking and zero-retention safeguards.

Architecture clues

  • Hand-offs preserve full conversational context for human support reps.
  • Requests can trigger authenticated actions such as applications or medical alarm exploration.
  • WhatsApp, email, and voice agents are planned on the same foundation.

Evidence from the source

"Most deinePflege customers rely on Germany's most popular messaging app, WhatsApp - and soon, Agentforce will provide full support there."
"This level of automation is expected to reduce the average resolution cost per case from $17 to just $2, saving approximately $300,000 annually."
"When customers reach out via email or phone with requests - like changing items in their care box - Agentforce can reason across contact history in Service Cloud and company FAQs, documents, and offerings in Data Cloud to confirm eligibility and guide them through next steps right away."
"deinePflege estimates that Agentforce will autonomously resolve 40% of support cases in seconds"
Transparency Evidence & methodology 100/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    5 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Salesforce

    deinePflege customer story

    First-party
    https://www.salesforce.com/customer-stories/deinePflege/
    Source type
    Vendor-published customer story
    Published
    Jun 18, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jun 18, 2025 · Salesforce · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.