PROVEN GROUND

The event backbone your business needs to operate in real time

We have been implementing Confluent across Latin America for 7 years, from Apache Kafka clusters in private data centers to Confluent Cloud on all three major clouds. Today, as IBM partners, that same platform is the foundation your agents run on.

Schedule a diagnostic

No commitment · 30 minutes · With a senior architect

  • 7 years implementing Confluent in the region
  • Banking, telco and retail in production
  • AWS, GCP, Azure and on-premise
WHY IT MATTERS

The nightly batch no longer cuts it

Most organizations move data by copying it: a job reads one database, writes to another and waits until the next night. That model worked while decisions could wait. When fraud, inventory or customer experience are settled in seconds, copying data stops being an architecture and becomes the problem.

Integrations that multiply

Every new system adds point-to-point connectors. Ten systems mean ninety possible integrations, and every one of them has to be maintained.

Data that arrives too late

By the time the report runs, the customer has hung up, the transaction has cleared and the stock is gone.

Nobody knows which version is right

With no schemas and no lineage, every team reads the same fields differently and the numbers never match.

Agents inherit the problem

An agent wired to a warehouse that refreshes overnight reasons about a past that no longer exists.

WHAT WE IMPLEMENT

From the first topic to full governance

We cover the entire lifecycle of the streaming platform, not just the install.

Platform

  • Confluent Cloud on AWS, GCP and Azure
  • Confluent Platform on-premise and hybrid
  • Sizing, high availability and disaster recovery
  • Multi-region and replication with Cluster Linking

Migration

  • From open source Apache Kafka to Confluent
  • From legacy queues such as MQ or JMS
  • Migration with no downtime window
  • Coexistence and progressive cutover by domain

Processing

  • Apache Flink SQL and streaming applications
  • Streaming Agents that run inside the stream
  • Real-Time Context Engine for RAG
  • Tableflow into the lakehouse

Governance

  • Schema Registry and contract evolution
  • Catalog, lineage and quality for data in motion
  • Security, RBAC and end-to-end encryption
  • Observability and cost control
HOW WE DELIVER

Three ways to work with us

From a short assessment to running your platform day to day.

  1. 2 to 4 weeks

    Platform assessment

    We review your current data architecture, your use cases and your streaming maturity. We pinpoint where real time changes a business outcome and what it takes to get there.

    Assessment report and roadmap

  2. 6 to 16 weeks

    Implementation and migration

    We deploy Confluent in your cloud or your data center, migrate existing workloads and integrate your systems. Your team takes part in every sprint.

    Platform in production and a trained team

  3. Monthly retainer

    Operations and evolution

    Monitoring, performance tuning, cost control and platform evolution as use cases and volume grow.

    Monthly report and priority support

USE CASES

Where streaming changes the outcome

Patterns we have taken to production with clients across the region.

Banking

Fraud detection inside the transaction

Payment events are scored against historical behavior and current context before authorization. The decision happens inside the transaction, not in tomorrow morning's report.

Banking

Core modernization without replacing the core

The core publishes its changes as events and digital channels consume them from there. Online banking and the app stop hitting the core directly, and migration can move domain by domain.

Telecommunications

Service quality and subscriber experience

Network telemetry feeds degradation detection and customer care from the same stream. The agent taking the call already knows there was an outage in the subscriber's area.

Retail

Inventory and pricing in sync across channels

Stores, e-commerce and the distribution center work off the same inventory state. No more selling what is out of stock, no more prices that differ by channel.

Cross-industry

Real-time context for AI agents

Flink builds and maintains the context agents query, so they answer with the current state of the business without rebuilding indexes or waiting on a batch job.

Is your data architecture ready to operate in real time?

Book 30 minutes with a senior architect. We look at your actual case and tell you what it would take. No sales pitch.