Movate x Lyzr — How Movate Chose Lyzr’s Agentic AI Over Agentforce
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Why Movate chose Lyzr’s Agentic AI over
Agentforce to power its enterprise AI workforce
A global IT and CX leader operating across 21 locations and 60 countries needed an agentic platform that could move beyond Salesforce’s walls. Lyzr’s private-first, stack-agnostic Agent Studio gave Movate full ownership of its AI, its data, and its outcomes.
Two companies, one shared conviction:
AI must perform in production, not just in demos
Movate operates at the intersection of enterprise IT and customer experience. Lyzr provides the agentic infrastructure that makes AI real at that intersection.
Platform-Agnostic by Design
Movate’s heterogeneous client environments span Salesforce, ServiceNow, SAP, and custom stacks. Lyzr agents run across all of them without forcing everything into a single ecosystem.
Private-First Deployment
Every agent deployment lives inside Movate’s own AWS VPC. Client data never leaves the secure boundary, and Movate retains full IP ownership with no hidden platform tax at scale.
Weeks, Not Quarters
Lyzr’s low-code Agent Studio and pre-built agent templates compressed Movate’s time from agent concept to production deployment, removing the months of custom engineering Agentforce would have required.
Responsible AI Built In
With Lyzr’s native hallucination manager, PII redaction, audit-ready logs, and role-based access, Movate could meet client compliance requirements without bolting on external governance layers.
A 12,000-person engineering and CX organization drowning in fragmented workflows and pilot-stage AI
Movate manages one of the most complex software delivery ecosystems in its segment, with engineering workflows distributed across Jira, GitHub, SharePoint, TestRail, and Rally simultaneously.
As client project volume grew, the increasing density of code changes, cross-system dependencies, and evolving documentation made it practically impossible for engineers and QA teams to maintain consistent velocity, accuracy, and governance.
At the same time, Movate’s leadership recognized a harder structural problem: the company’s AI pilots were stalling at proof-of-concept, unable to cross the threshold into governed, repeatable production systems. A platform decision was needed that would set the standard for how every future agent would be built, deployed, and operated.
Invisible Change Impact
Engineers manually traced dependencies across five disconnected systems to understand how a single code modification might cascade into broken APIs, failed test cases, or downstream service outages, a process that consumed hours per sprint.
Fragmented QA Cycles
Test case preparation was manual, inconsistently applied, and disconnected from the live codebase. QA teams were duplicating effort across sprints because there was no shared intelligence layer linking tickets to tests to repositories.
Agentforce Ecosystem Lock-In
Agentforce’s deep Salesforce dependency made it unsuitable for Movate’s mixed-stack delivery environments. Deploying it at scale would have required reshaping client processes around a single ecosystem rather than the other way around.
No Unified AI Governance
With early GenAI deployments spreading across teams and tools, Movate needed a control plane that could enforce consistent guardrails, audit activity, and ensure data residency across all agents, not as an afterthought but as a foundation.
Movate deploys a unified AI Pod built on Lyzr Agent Studio, operating inside a secure private AWS environment
Lyzr’s Agent Studio was integrated directly into the MovateAI Platform, enabling rapid delivery of specialized, context-aware agents across software delivery, QA, data engineering, IT operations, and customer experience.
Change Impact Analysis Agent
Ingests commits from GitHub and tickets from Jira in real time, automatically mapping which services, APIs, and test cases a given change will affect, replacing hours of manual dependency tracing.
Intelligent Test Generation Agent
Reads the unified knowledge graph to auto-generate relevant test cases aligned to each sprint’s scope, pulling context from TestRail, Rally, and the current branch state simultaneously.
Semantic Code Search and Generation Agent
Enables engineering teams to query the entire codebase in natural language, surface reusable patterns, and generate new code that automatically conforms to established repository conventions and standards.
Unified Knowledge Graph
A continuous ingestion layer pulls data from Jira, GitHub, SharePoint, TestRail, and Rally into one relationship-aware graph, powering every agent with real-time, contextually accurate information.
Centralized Administration and Audit Controls
Role-based access, agent entitlements, audit-ready activity logs, and protocol enforcement ensure that every agent in the fleet operates within defined boundaries, fully observable and compliant.
Private AWS VPC Environment
All agents run inside Movate’s own cloud environment with zero data leaving the perimeter, meeting the data residency and compliance requirements of Movate’s most security-conscious enterprise clients.
From platform decision to production agents in eight weeks
Lyzr’s structured engagement model meant Movate never had to figure out the path alone. Each phase had defined deliverables, clear milestones, and agents shipping to real workflows.
Discovery and Platform Decision
Movate’s engineering and AI leadership evaluated Lyzr Agent Studio against Agentforce across four dimensions: ecosystem flexibility, data sovereignty, governance depth, and total cost of ownership. The heterogeneous client stack and private-cloud requirement made Lyzr the clear fit. Procurement was completed through Lyzr’s AWS Marketplace private offer, streamlining compliance and billing.
Knowledge Graph Construction and Connector Setup
Lyzr’s integration layer was connected to Movate’s live instances of Jira, GitHub, SharePoint, TestRail, and Rally. A continuous ingestion pipeline was configured to hydrate the central knowledge graph in real time, creating the context engine that every subsequent agent would rely on for accurate, relationship-aware outputs.
Agent Build and Internal Testing
Using Lyzr Agent Studio’s low-code builder and developer SDK, Movate’s team co-designed the Change Impact Analysis Agent, the Test Generation Agent, and the Semantic Code Agent. Each agent was tested against real sprint data, refined for accuracy, and reviewed against Movate’s internal governance standards before any client-facing exposure.
Private AWS Deployment and Rollout
The full agent fleet was deployed into Movate’s private AWS VPC with role-based access controls, audit logging, and centralized administration activated. Engineering and QA teams across delivery pods onboarded through two interfaces: a Connector Platform for system-level integration and the Lyzr Agent UI for day-to-day workflow automation.
Expansion Across IT Operations and CX Delivery
With the SDLC AI Pod proven, Movate extended the same Lyzr-powered architecture into IT operations, data engineering, and customer experience delivery, executing on its W(AI)VE framework of augmenting human delivery pods with intelligent digital twins at every stage of the value chain.
How data flows from source systems to governed agent outputs
A two-pillar architecture combining a live knowledge graph with a layered multi-agent framework, all operating within Movate’s sovereign AWS boundary.
Enterprise Source Systems
Jira, GitHub, SharePoint, TestRail, Rally — continuous real-time ingestion
Unified Knowledge Graph
Relationship-aware, real-time graph powering all agent context and reasoning
Lyzr Agent Studio
Multi-agent fleet with entitlements, protocol enforcement, and governance chassis
Private AWS VPC
Zero-trust isolation, IAM, audit logs, RBAC, full data residency control
Automated Delivery Actions
Impact reports, test suites, code generation, CX routing, IT ops resolution
Lyzr vs. Agentforce: the decision matrix that shaped Movate’s choice
Movate evaluated both platforms across the criteria that matter most for a global IT services organization serving clients on mixed technology stacks.
Production results from Movate’s Lyzr-powered SDLC AI Pod
Measurable improvements observed across engineering velocity, QA consistency, and governance coverage once the agent fleet went live in Movate’s private AWS environment.
Reduction figures reflect production measurements from Movate’s engineering organization post-deployment. Additional outcomes across IT operations and CX domains are being measured as agent expansion continues.
Our partnership with Lyzr marks an important moment in our AI journey, bringing our strategy of augmenting humans with digital twins to reality. By partnering with Lyzr, we are not just accelerating AI deployment, we are transforming how enterprises harness AI across their entire value chain. Our clients can now deploy contextually intelligent agents faster to realize business impact.
Movate’s deep IT services expertise, combined with our Agent Studio, creates a compelling value proposition for enterprises. Together, we are building an ecosystem where AI agents are not just tools. They are intelligent collaborators that understand context, adapt to business needs, and deliver measurable outcomes. This partnership accelerates the path from AI experimentation to enterprise-wide transformation.
The Lyzr infrastructure Movate is built on
Lyzr is the full-stack agentic infrastructure that takes enterprises from diagnosis to production, combining the flexibility of open-source with the security controls of a managed enterprise platform.
Multi-Agent Orchestration
Deploy interconnected networks of specialized agents that collaborate autonomously on complex workflows, with defined roles, permissions, and handoffs across departments and systems.
Learn moreKnowledge Graph Architecture
A continuously updated, relationship-aware knowledge base that gives every agent real organizational context, connecting tickets, code, documentation, and test data into one coherent intelligence layer.
Learn moreBuilt-In Governance and Compliance
Native hallucination manager, PII redaction, toxicity controls, explainability layer, and a full audit trail. Governance is a structural property of the platform, not an add-on that slows deployment.
Learn morePrivate VPC and On-Premise Options
Run Lyzr entirely within your own cloud perimeter. No data leaves your environment. Client IP remains yours. Supports AWS, Azure, GCP, and on-premise deployments with 48-hour integration SLAs.
Learn moreNo-Code to Full-Code Agent Studio
Business users design agents visually with no-code tools. Developers extend via SDK and full-code workflows. Both paths share the same governance chassis, so speed never compromises control.
Learn moreOpen Model Architecture
Deploy agents on OpenAI, Anthropic, Google, open-source models, or your own fine-tuned models. No vendor lock-in at the model layer. Movate can optimize cost and performance independently of any single AI provider.
Learn moreMove your enterprise AI from pilot to production
Whether you are building a specialized agent fleet, evaluating platforms against Agentforce, or ready to deploy governed AI across your SDLC and CX workflows, our team will give you a real conversation, not a sales pitch.