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IBM Financial Services Brazil

Inter

Customer Service Automation · IT Operations Automation

Inter needed to evolve a large, API-heavy conversational banking environment into a more scalable AI operating model without breaking the integrations, governance controls, and continuity behind critical customer self-service journeys.

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45M customers served
>180 products supported across digital journeys
approximately 700 hours of work
more than 350 manual JSON deployments

Reported impact

Business outcome

Inter reduced deployment effort dramatically, preserved continuity across customer-facing banking journeys, and created a scalable governance-led foundation for expanding agentic AI across a 45 million-customer financial platform.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Inter established an orchestration foundation for its banking AI operations by deploying IBM watsonx Orchestrate on IBM Cloud and migrating its existing assistant estate onto that layer. The bank's Seven assistant already supported more than 180 products, around 80 transactional journeys, and more than 100 APIs, so the new architecture had to preserve continuity while enabling more contextual experiences. IBM and Inter transitioned all 18 assistants while keeping integrations and access controls intact, then used watsonx Orchestrate APIs to automate operational tasks such as deployments and governance workflows. The platform now coordinates multiple AI agents across self-service journeys including address updates, credit-limit inquiries, card replacements, and payroll-loan tracking. Inter also set up a Center of Excellence to standardize development and governance, turning its large conversational environment into a reusable operating model for future agentic banking initiatives.

Data flow

Customer requests flow through Inter's AI environment, where watsonx Orchestrate coordinates the agents and service integrations behind banking self-service journeys on IBM Cloud, while deployment APIs automate the release and governance processes needed to keep those journeys up to date.

Solution architecture

2 components · 1 layer
  1. Orchestration
    • IBM watsonx Orchestrate Coordinates AI agents and automates deployment and governance activities across Inter's banking journeys.
    • IBM Cloud Hosts the orchestration foundation used to run Inter's conversational and agentic banking services.

Architecture clues

  • All 18 assistants were transitioned while preserving integrations and governance controls.
  • Inter automated deployment processes through watsonx Orchestrate APIs.
  • The bank created a Center of Excellence for AI development standards and governance.

Evidence from the source

All 18 assistants were successfully transitioned while preserving the integrations, governance controls and operational continuity
Building on eight years of strategic collaboration with IBM, Inter established a scalable AI orchestration foundation powered by IBM watsonx Orchestrate on IBM Cloud
The bank also automated deployment processes through watsonx Orchestrate APIs
an estimated 95% reduction in deployment effort
serving more than 45 million customers
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
    2 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

    Inter customer story

    First-party
    https://www.ibm.com/case-studies/inter
    Source type
    Vendor-published customer story
    Published
    Aug 11, 2026
    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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