Globant

globant.com

Globant’s documented scope extends beyond strategy into system development, production deployment, maintenance, and managed operations. Its practices include software engineering, AI, CloudOps, Microsoft, Salesforce, and managed cybersecurity. Procurement should distinguish advisory deliverables from implementation and operating responsibilities: the portfolio also includes AI-assisted engineering services and proprietary platforms, which are different purchases from custom AI development. ^[1] ^[2] ^[3] ^[4] ^[5] ^[6] ^[7] ^[8]

Services and delivery

AI adoption and use-case advisory

Advisory. Identifies AI opportunities, develops adoption plans, and determines how AI can fit into customer operations. This is planning work rather than a commitment to implement a production system. ^[2]

Custom AI development and deployment

Implementation. Develops tailored AI algorithms, products, and platforms and prepares them for production. The offering also includes customizing AI-agent functionality and interactions for customers’ software-development lifecycles. ^[2]

AI solution operations

Managed services. Maintains, calibrates, and operates deployed AI solutions at scale. Buyers should establish the contractual division of responsibility for model performance, monitoring, and incidents. ^[2]

Azure data platforms and AI implementation

Implementation. Designs and implements Azure data platforms and AI-driven solutions, including AI integration, workflow automation, predictive analytics, and MLOps practices. ^[4]

Software engineering and modernization

Implementation. Builds web, native mobile, Flutter, and hybrid applications. Delivery spans design, implementation, testing, microservices, legacy modernization, and maintenance or enhancement of existing software. ^[1]

Technology architecture advisory

Advisory. Produces technology strategies, adoption plans, and architecture roadmaps through a separately described architecture consulting offering. Implementation should be scoped independently. ^[1]

Cloud strategy advisory

Advisory. Assesses cloud costs and readiness, develops architecture, and plans adoption through the Microsoft practice. These advisory activities are distinct from migration execution. ^[4]

Cloud infrastructure and migration

Implementation. Constructs cloud infrastructure and executes migrations through the CloudOps practice. Resilient-architecture design is also documented; platform-specific migration scope requires separate confirmation. ^[3]

Cloud operations and reliability

Managed services. Provides operational support, site reliability engineering, cloud cost management, and chaos engineering. The CloudOps page also specifies 24/7 support for its migration service. ^[3]

Microsoft business-application implementation

Implementation. Configures and integrates Dynamics 365 and Power Platform business applications. This offering concerns application implementation, separate from the practice’s Azure AI services. ^[4]

Microsoft managed services

Managed services. Provides Azure and Microsoft 365 monitoring, cost optimization, resilience, security, pipeline automation, and infrastructure as code. The practice describes 24×7×365 coverage. ^[4]

Managed cybersecurity operations

Managed services. Operates an outsourced CyberSOC with SIEM operations, event escalation, and remediation. AWS-oriented services include vulnerability checks, threat detection and response, network monitoring, and data-privacy event handling. ^[6]

Salesforce implementation and integration

Implementation. Configures, develops, and integrates Salesforce systems. The practice distinguishes implementation from its architecture, advisory, and change-management activities. ^[5]

Agentforce agent development

Implementation. Builds and customizes Salesforce Agentforce AI agents. This is separately evidenced AI implementation, rather than an inference from Salesforce credentials or general platform services. ^[5]

AI Pods engineering delivery

Implementation. Uses AI agents under human supervision to deliver migrated modules, dependency upgrades, regression suites, decomposed monoliths, microservices, and release packages. Purchased software deliverables, not internal AI use, determine this classification. ^[7]

AI Pods architecture assessment

Advisory. Provides assessment and strategy deliverables including dependency maps, architecture decisions, and risk-ranked roadmaps. These Pods are advisory rather than software implementation. ^[7]

Glob.AI OS platform

Software product. Provides an AI platform for customized agents and agentic processes, with orchestration, governance, integration, and security and cost controls. Platform access is distinct from implementation services. ^[8]

Technology publications

Research. Publishes reports, books, webinars, and blogs about technology trends. These informational materials do not establish implementation or managed-service capabilities. ^[9]

Company details

Technology and platforms

The Microsoft practice documents migration and modernization of applications, infrastructure, data, and SAP environments using Azure Migrate, App Services, and SQL migration tools. It also offers Dynamics 365 and Power Platform implementation, alongside Azure data and AI delivery. ^[4]

Globant Enterprise AI is presented as a platform within the AI practice. Like Glob.AI OS, platform access should be distinguished from separately scoped advisory, integration, development, and operating services. ^[2] ^[8]

Engagement and delivery

AI Pods combine agent-executed work with expert supervision and identify concrete engineering or assessment outputs. Buyers should specify whether the engagement purchases delivered software, an architecture assessment, custom AI functionality, or platform access; those scopes carry different acceptance and support requirements. ^[7]

Track record

For an unnamed pharmaceutical manufacturer, Globant reports forming a blended client–Globant data-science team, standardizing ERP data from two facilities, building a data pipeline, and developing custom machine-learning models to predict manufacturing duration and waiting times. It reports working with AWS to put initial models into production at both sites and providing predictions through a planner interface. Further models and site expansion were described as continuing or future work. The case supplies no numerical accuracy benchmark. ^[10]

For an unnamed telecommunications customer, Globant reports implementing AWS network controls, monitoring, infrastructure automation, and IAM policies. The case names AWS WAF, CloudFront, API Gateway, Application Load Balancer, Route 53, Security Hub, CloudWatch, S3/Athena, and GitLab/GitOps. It also describes role- and attribute-based authorization and secure pipeline components. These are Globant’s reported delivery activities, not independently verified outcomes. ^[11]

Scope and limitations

The supplied evidence establishes several purchasable technology services, but does not provide project pricing, minimum engagement sizes, staffing commitments, or contractual service levels.
The pharmaceutical and telecommunications case studies are anonymous. They support specific delivery experience but provide limited independent validation or quantitative performance context.
Two additional case-study pages returned iframe-only content during the supplied research. Their substantive claims were not verified and are not used here.
Research access gaps do not demonstrate that a capability is absent. This profile is limited to the offerings and delivery evidence documented in the supplied notes.

Questions to ask

Can Globant provide named references matching our use case, technology stack, regulatory requirements, and production scale?
Who owns model evaluation, deployment, monitoring, recalibration, and incident response after an AI system enters production?
Which platform subscriptions, model-provider charges, implementation fees, and ongoing support costs are separate?
For AI Pods, how are acceptance criteria, capacity, rework, code ownership, and exit arrangements defined?
Which services and environments receive continuous coverage, and what response, restoration, escalation, and security obligations are contractual?
What data-handling, intellectual-property, model-provider, and platform constraints apply to the proposed solution?

Overview