Migration Services
Amazon Lex to Conversational Agents Migration Services
Move Amazon Lex bots to Conversational Agents through a structured migration focused on stronger conversation control, generative AI, and reliable customer experiences.
Migration Services
Move Amazon Lex bots to Conversational Agents through a structured migration focused on stronger conversation control, generative AI, and reliable customer experiences.
Why Conversational Agents?
Use flows, pages, routes, conditions, and forms to manage complex and multi-step conversations clearly.
Introduce generative playbooks for flexible conversations while keeping critical business processes controlled.
Connect approved websites, documents, Cloud Storage, and BigQuery data to generate more relevant responses.
Connect agents with Vertex AI, Gemini, BigQuery, Cloud Functions, Cloud Run, Contact Center AI, and other Google Cloud services.
How We Migrate
Review Lex bots, locales, intents, sample utterances, slots, slot types, prompts, Lambda functions, aliases, channels, analytics, and dependencies.
Map existing customer journeys into flows, pages, routes, forms, playbooks, data stores, webhooks, and reusable conversation components.
Recreate intents, entities, parameter collection, prompts, confirmation steps, fallback handling, responses, and conversation transitions.
Adapt Lambda logic, APIs, authentication, telephony, messaging channels, session data, analytics, and connected business systems.
Validate complete conversations, language understanding, parameter collection, integrations, latency, fallback behavior, and business outcomes.
Why Codimite?
Codimite combines Google Cloud expertise, conversation design, application integration, generative AI, and structured quality assurance.
Start Your MigrationComplete Lex Bot Discovery. We identify active intents, slots, prompts, Lambda hooks, channel dependencies, fallback paths, and unused bot assets.
Conversation Architecture Redesign. We translate intent-based interactions into clear flows, pages, forms, routes, playbooks, and escalation paths.
Fulfillment Modernization. We move Lambda-based validation and fulfillment into secure Google Cloud webhooks, APIs, and service integrations.
Controlled Production Rollout. We reduce risk through regression testing, pilot users, parallel operation, phased traffic, monitoring, and rollback planning.
Platform Comparison
Both platforms support voice and text bots, but Conversational Agents provides stronger orchestration, generative AI, and Google Cloud integration.
| Area | Amazon Lex | Conversational Agents |
|---|---|---|
| Platform approach | AWS conversational interface service organized around bots, intents, slots, and fulfillment | Google Cloud conversational AI platform combining structured flows, generative playbooks, and grounded data |
| Conversation structure | Intents contain utterances, slots, prompts, confirmation, and fulfillment behavior | Flows and pages organize conversations into clear, reusable states |
| Conversation control | Intent steps, slot order, conditions, next actions, and session state guide the conversation | Routes, conditions, pages, forms, event handlers, and session parameters provide explicit control |
| Intent recognition | Sample utterances train the bot to identify user goals | Reusable intents and route matching connect user goals to the correct conversation state |
| Parameter collection | Slots collect required values for an intent | Page forms and session parameters collect, validate, and reuse structured information |
| Slot types | Uses built-in and custom slot types | Uses system and custom entity types to identify parameter values |
| Prompts and retries | Slot prompts support retry settings, variations, and failure responses | Form parameters support prompts, validation, reprompting, no-match, and no-input handling |
| Confirmation | Intent confirmation asks users to approve collected slot values | Confirmation can be designed using routes, conditions, responses, and reusable pages |
| Fallback handling | Uses the built-in fallback intent and configured retry behavior | Uses no-match and no-input event handlers at agent, flow, or page level |
| Fulfillment | Commonly invokes AWS Lambda through dialog and fulfillment code hooks | Uses webhooks and tools connected to Cloud Run, Cloud Functions, APIs, and enterprise systems |
| Generative AI | Primarily intent-led, with generative capabilities requiring additional AWS services | Generative playbooks can answer questions, call tools, and hand off to deterministic flows |
| Knowledge grounding | Knowledge and search capabilities depend on connected AWS services and architecture | Data stores can ground responses in approved websites, documents, Cloud Storage, and BigQuery data |
| Voice support | Supports text and speech interactions and integrates with Amazon Connect | Supports voice and text experiences, telephony integrations, and Google Contact Center AI use cases |
| Streaming conversations | Supports streaming conversations and wait-and-continue behavior | Supports streaming and telephony interactions based on the selected integration |
| Languages | Bot locales contain independent intents, slots, and slot types | Supports multilingual agents, language-specific resources, and localized responses |
| Testing | Console testing and bot analytics support intent, slot, and conversation analysis | Simulator, reusable test cases, validation, environments, and regression testing support controlled releases |
| Versions and deployment | Bot versions and aliases control deployment environments | Versions and environments support controlled testing and production deployment |
| Analytics | Tracks intents, slots, utterances, conversations, and fulfillment outcomes | Supports conversation analysis across flows, pages, routes, intents, and agent behavior |
| Security | Uses AWS IAM, resource policies, encryption, logging, and AWS network controls | Uses Google Cloud IAM, service accounts, private networking, encryption, audit logs, and data controls |
| Cloud ecosystem | Closely integrated with AWS Lambda, Connect, CloudWatch, and other AWS services | Closely integrated with Vertex AI, Gemini, BigQuery, Cloud Run, and Google Cloud services |
| Best suited for | Conversational applications built primarily within AWS | Complex customer journeys, contact centers, grounded assistants, and generative conversational applications on Google Cloud |
FAQs
We can migrate intents, utterances, slots, slot types, prompts, responses, fulfillment logic, languages, integrations, and connected conversational workflows.
No complete one-click migration is available. Lex bot assets must be assessed, mapped, rebuilt, integrated, and validated within Conversational Agents.
Intent goals, utterances, slot definitions, and core business logic may be reusable. Routing, parameter handling, AWS-specific code, authentication, and webhook formats usually require changes.
Each Amazon Connect, telephony, web, or messaging integration must be redesigned for the selected Google Cloud or partner channel, including authentication, payloads, session handling, and escalation.
Yes. Generative playbooks and grounded data stores can support flexible FAQ and discovery experiences, while transactional and sensitive workflows remain controlled through deterministic flows.
We test intent recognition, parameter capture, prompts, fulfillment, integrations, fallback handling, latency, completion rates, and business outcomes before production cutover.
Assess your Lex bots, intents, slots, fulfillment, channels, and customer journeys to build a practical Conversational Agents migration roadmap.
Start Your Migration
