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Microsoft Software / SaaS Czechia

VOCALLS

Customer Service Automation · Enterprise Knowledge Search · Fraud Detection

The company excels in understanding complex telephone systems and contact centers.

Read the original story Explore all use cases
Its happy customer, Estafeta, has seen myriad benefits: a 78% reduction in average handling time aside from a 120% increase in answered calls.
Previously, Estafeta's customers had to navigate a lengthy interactive voice response (IVR) labyrinth and spent up to 10 minutes in the queue waiting to speak...
Relying on Microsoft Azure AI technologies, VOCALLS automates over 50 million interactions per year.
We automate more than 50 million conversations annually

Reported impact

Business outcome

"We develop voicebots that can constantly evolve and cut costs.

  • Customer Experience
  • Productivity Improvement
  • Revenue Growth
  • Risk Reduction

Solution

VOCALLS used Azure OpenAI Service, Azure AI Search, Azure Cosmos DB to replace disconnected manual workflows with a more consistent digital operating model. Low-code automation and copilot capabilities orchestrate tasks, route work, and surface context to agents or business users without requiring separate point solutions. Where generative AI is involved, Azure OpenAI handles the language understanding layer while connected data and workflow services keep responses grounded in enterprise context. It also connects with surrounding systems such as Call-center telephony, which lets the new Azure-based workflow fit into existing operations rather than standing apart from them. "We develop voicebots that can constantly evolve and cut costs.

Data flow

Content and operational context are prepared in Azure AI Search, passed to Azure OpenAI for generation or extraction, stored in Azure Cosmos DB, and returned through the user-facing application to employees or customers with grounded responses.

Solution architecture

5 components · 4 layers
  1. Compute
    • Azure OpenAI Service Runs large language model inference for summarization, extraction, conversational AI, and grounded answers.
    • Azure AI Services Supplies prebuilt AI capabilities such as language, speech, or vision services within the application flow.
  2. Storage
    • Azure Cosmos DB Persists low-latency application data, conversation state, or operational records.
  3. Serving
    • Azure AI Search Indexes enterprise content and retrieves grounding context for assistants and search experiences.
  4. Orchestration
    • Power Platform Provides the low-code automation and application platform for workflow modernization.

Architecture clues

  • Applies retrieval-based grounding with Azure AI Search before answer generation.
  • Uses Azure OpenAI for grounded generation or large-scale extraction workloads.

Evidence from the source

"We develop voicebots that can constantly evolve and cut costs.
"We fell in love with the challenge and innovation of conversational AI, and we hope to help more companies deliver better customer service while supporting their business objectives." "We automate more than 50 million conversations...
"We use various AI technologies, including Azure AI Search and Azure Cognitive Services, to ensure that our voicebots are trained in every facet of interaction," explains Martin Čermák, CTO of VOCALLS.
Předota agrees and adds, "When Microsoft launched Azure OpenAI Service, we knew we could use it to enhance our voicebots even further." A compelling success story One of VOCALLS's happy customers, Estafeta, is a pioneer in logistics and...
The company excels in understanding complex telephone systems and contact centers.
Transparency Evidence & methodology 88/100 reference value · 87% 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 value88/100
  • Problem clarity12/20
    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 specificity16/20
    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 confidence87%
  • 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 specificity8/10
    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. Microsoft

    VOCALLS customer story

    First-party
    https://www.microsoft.com/en/customers/story/1725778377710136622-vocalls-azure-telecommunications-en-czechia
    Source type
    Vendor-published customer story
    Published
    Jan 16, 2024
    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 Jan 16, 2024 · Microsoft · 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.

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