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ScAIfe

Call Centers: AI for call centers that assists your agents in real time and improves resolution rates.

Intelligence in every conversation: from the agent copilot to the models that decide when and how to contact each customer.

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  • Higher productivity
  • Higher recovery
  • More effective contact

Founder's case · AI agent

Autonomous resolution

Payment claims · Financial institution

  1. Claim received

    Payment not reflected

  2. Classification

    Conversational analysis of the claim

  3. Real-time lookup

    External provider via API

  4. Resolution

    Refunds the money or sends the receipt

95%

fewer claims escalated to human agents

Recreation of the flow implemented in a financial institution's call center.

Sound familiar?

High volume, manual work and decisions without data.

  • Your agents waste time manually classifying every call
  • You don’t know when or through which channel to contact each customer
  • It’s hard to predict which debtors will pay

These are exactly the problems we solve.

Capabilities

How we boost productivity, recovery and effective contact

  1. 01
    HIGHER PRODUCTIVITY

    Real-time agent copilot

    While the conversation is underway, the agent sees reply suggestions, customer context and recommended next actions on screen. Less time searching for information, more time resolving issues.

    What it delivers

    • Lower average handling time
    • Higher first-contact resolution
    • Faster agent onboarding
  2. 02
    HIGHER RECOVERY

    Propensity-to-pay model

    Predicts which customers are most likely to pay in the coming days, so your collections team can prioritize its work and focus resources where the impact is greatest.

    What it delivers

    • Smart portfolio prioritization
    • Higher recovery with the same team
    • Data-driven decisions, not gut feeling
  3. 03
    MORE EFFECTIVE CONTACT

    Optimal contact channel and time

    Determines, for each customer, the best channel (call, WhatsApp or email) and the time of day with the highest probability of effective contact.

    What it delivers

    • Higher effective contact rate
    • Fewer failed attempts per agent
    • Less intrusive customer experience
  4. 04
    HIGHER PRODUCTIVITY

    Automatic call classification

    Analyzes every call, identifies the reason for contact and classifies it automatically, without the agent filling in a single form. The data is available in real time.

    What it delivers

    • Zero time spent on manual classification
    • 100% consistent data
    • Real-time visibility into contact reasons

Projects

What we’ve already built

Systems and AI agents running in real operations.

Founder’s caseCall Center · Financial institution

AI agent for the autonomous resolution of payment claims

95%

reduction in claims escalated to human agents

Problem

  • Customers contacted the call center about payments that hadn’t been reflected
  • The process was 100% manual: the agent checked external systems and cross-referenced data with the back office
  • High volume, with slow, people-dependent handling

How it works

  • Classifies the claim through conversational analysis
  • Queries the external provider in real time via API
  • Resolves the claim autonomously: refunds the money or sends the receipt, depending on the case

This is the same project we feature as the “Founder’s case” on our home page, told from a call center perspective.

Implemented caseCall Center · Collections

Automated collections back office

Result

  • Lower operational workload
  • Significantly shorter processing times

Why ScAIfe?

Companies know they need technology, but they don't know where to start or how to turn it into concrete results.

ScAIfe was born to close that gap, with two complementary profiles: business and technical execution.

  • 15+ years in banking & fintech
  • Fintech Américas Award
  • AI applied to real processes
Meet the team

  • Sergio Orcellet

    Founder & CEO

    15+ years at Banco Galicia leading digital products and operations in banking and fintech. Financial Innovation Award, Fintech Américas 2026.

  • Kevin Soulier

    Co-Founder & CTO

    10+ years in enterprise software engineering. Currently builds production AI at EY. Master's in Artificial Intelligence in progress (Universidad de San Andrés).

FAQ

AI for call centers: what you need to know

What AI solutions do you offer for call centers?

We apply AI on four fronts: a real-time agent copilot, a propensity-to-pay model, a model for the optimal contact channel and time, and automatic call classification. Each one targets higher productivity, higher recovery or more effective contact.

How does AI help agents during a call?

With the copilot, agents see reply suggestions, customer context and recommended next actions on screen while the conversation is underway. And automatic classification tags every call without them having to fill in a single form.

How does AI improve collections?

The propensity-to-pay model predicts which customers are most likely to pay in the coming days, so your team can prioritize its work. The optimal channel and time model tells you when and through which channel (call, WhatsApp or email) to contact each customer.

Do you have real call center cases?

Yes. The “Founder’s case” features an AI agent that autonomously resolves payment claims in a financial institution’s call center: it achieved a 95% reduction in claims escalated to human agents. We also implemented an automated collections back office, with a lower operational workload and significantly shorter processing times.

How do we get started?

Tell us about your operation’s challenge and together we’ll define which model will have the most impact in your case. The diagnosis is free and comes with no commitment, and we reply within 24 hours.

Contact

What challenge is your operation facing?

Every call center is different. Tell us the problem and together we’ll define which model will have the most impact in your case.

How do we start?

  1. 01

    Discovery call

    We understand your business and identify where technology can generate the greatest impact.

  2. 02

    Business and technology analysis

    We evaluate the problem from both a business and a technology perspective to define the best approach.

  3. 03

    Proposal

    We design a solution aligned with concrete results.

  4. 04

    Implementation

    We execute and deliver a solution ready to generate value.

  • We validate before building
  • Experience in real business solutions
  • End-to-end support

We reply within 24h

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