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IBM Commercial and Professional Services Middle East

Inspire

Customer Service Automation · IT Operations Automation

Inspire needed to reduce the manual effort in routine HR tasks so employees could complete leave, expense, and insurance requests quickly and the company could offer a more modern employee experience to attract and retain talent.

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15% boost in productivity, driving business growth and efficiency
15% decrease in costs, resulting in significant cost savings
15% reduction in employee time, freeing resources for higher-value tasks
450 employees

Reported impact

Business outcome

Inspire reduced employee time and operating costs, improved HR productivity, and built a secure on-premises conversational platform it can keep expanding with new models and speech capabilities.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement

Solution

Inspire built an internal HR virtual assistant on IBM watsonx Assistant and trained it with Meta Llama 3 models through IBM watsonx.ai. The assistant is embedded in the company's internal portal, where employees can ask HR questions in natural language and complete transactional requests such as booking leave, submitting expenses, or requesting health-insurance forms. Behind the scenes, the assistant uses APIs to reach the required HR systems and complete those actions in real time rather than merely answering FAQs. Inspire and IBM also worked with the IBM Build Lab to stand up an on-premises platform powered by watsonx.ai and watsonx Assistant in the data center, which gave the company a secure base for future enhancements. With the new HR automation layer in place, the company can tune models, consider a future move to Granite, and add speech interfaces while preserving a unified conversational front end for employees.

Data flow

Employees interact with the HR assistant in the company portal, watsonx Assistant interprets the request using models trained in watsonx.ai, the workflow calls HR-system APIs to execute tasks such as leave bookings or expense requests, and the result is returned to the employee in real time.

Solution architecture

3 components · 2 layers
  1. Compute
    • Meta Llama 3 Supplies the large language models that Inspire fine-tuned for its HR assistant.
    • IBM watsonx.ai Supports model training and the on-premises AI platform that powers the assistant.
  2. Serving
    • IBM watsonx Assistant Provides the employee-facing conversational interface for HR questions and tasks.

Architecture clues

  • Inspire and IBM Build Lab deployed the platform on premises in the data center.
  • The assistant is embedded directly into the internal portal rather than exposed as a separate tool.
  • The company is considering switching from Meta Llama 3 to IBM Granite models and adding speech services.

Evidence from the source

15% boost in productivity
15% decrease in costs
Behind the scenes, the conversational AI receives the request, accesses the necessary HR systems through APIs, and makes the booking in real time.
It’s built on large language models from Meta Llama 3, which the company trained by using IBM watsonx.ai
The new solution deployed by Inspire is an AI conversational virtual assistant created with IBM watsonx Assistant
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
    3 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
    5 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. IBM

    Inspire customer story

    First-party
    https://www.ibm.com/case-studies/inspire
    Source type
    Vendor-published customer story
    Published
    May 19, 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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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