Data and AI automation in Creatio
We migrate data while preserving relationships and configure AI agents for scoring, classification, information processing, and task routing.
Data and AI automation in Creatio
We migrate data while preserving relationships and configure AI agents for scoring, classification, information processing, and task routing.
Quality data is the foundation of effective AI automation
AI delivers measurable results only with high-quality, structured data and controlled processes. We therefore design migration, the data model, access rights, and intelligent automation as one connected framework.
We cleanse and normalize data, remove duplicates, preserve relationships, and test imports first. Then we add AI scoring, classification, information processing, and routing with human oversight, constraints, and measurable quality metrics.
Quality data is the foundation of effective AI automation
AI delivers measurable results only with high-quality, structured data and controlled processes. We therefore design migration, the data model, access rights, and intelligent automation as one connected framework.
We cleanse and normalize data, remove duplicates, preserve relationships, and test imports first. Then we add AI scoring, classification, information processing, and routing with human oversight, constraints, and measurable quality metrics.
From data to practical AI automation
We build a unified foundation for data and intelligent automation: migrating information from legacy systems, configuring Creatio AI agents, and implementing practical use cases for sales, service, and operations.
Controlled data migration
We migrate reference data, records, and interaction history, removing duplicates, preserving relationships, and checking integrity.
AI agent configuration
We configure AI agents' roles, instructions, data sources, access permissions, and action limits for specific processes.
Intelligent request processing
We identify the topic, intent, and priority of each request, extract key information, and prepare the next step.
Sales scoring and prioritization
We score leads and opportunities based on profiles, history, and activity, helping salespeople focus on the most promising opportunities.
Intelligent document analysis
We extract details and terms from emails, contracts, and forms, turning unstructured content into Creatio data.
Operational task routing
We assign tasks based on request type, SLA, skills, and workload, with automatic escalation of exceptions.
From data to practical AI automation
We build a unified foundation for data and intelligent automation: migrating information from legacy systems, configuring Creatio AI agents, and implementing practical use cases for sales, service, and operations.
Controlled data migration
We migrate reference data, records, and interaction history, removing duplicates, preserving relationships, and checking integrity.
AI agent configuration
We configure AI agents' roles, instructions, data sources, access permissions, and action limits for specific processes.
Intelligent request processing
We identify the topic, intent, and priority of each request, extract key information, and prepare the next step.
Sales scoring and prioritization
We score leads and opportunities based on profiles, history, and activity, helping salespeople focus on the most promising opportunities.
Intelligent document analysis
We extract details and terms from emails, contracts, and forms, turning unstructured content into Creatio data.
Operational task routing
We assign tasks based on request type, SLA, skills, and workload, with automatic escalation of exceptions.
Data migration that preserves relationships and history
We map fields, reference data, and relationships and identify duplicates, gaps, and conflicting values. Transformation rules are recorded in the migration map.
Trial imports confirm completeness and referential integrity. Production cutover includes a migration plan and reconciliation procedures.
Migration that preserves relationships and history
We map fields, reference data, and relationships and identify duplicates, gaps, and conflicting values. Transformation rules are recorded in the migration map.
Trial imports confirm completeness and referential integrity. Production cutover includes a migration plan and reconciliation procedures.
From source data to controlled AI automation
We prepare the data, verify migration, and launch AI scenarios in a controlled environment. At each stage, we document the outcome and readiness criteria for the next step.
Data inventory
We identify data sources, owners, volumes, and structure, documenting reference data, business records, transaction history, and dependencies between objects.
Data quality profiling
We assess data completeness, formats, and freshness, identifying duplicates, gaps, inconsistencies, and broken relationships.
Cleansing and normalization
We remove duplicates, standardize values, agree on transformation rules, and map fields between systems.
Test and production migration
We run trial imports and verify completeness and referential integrity. After acceptance, we execute the agreed production migration plan.
AI use case configuration
We connect AI agents to prepared data and define instructions, constraints, and rules for delivering results to Creatio users.
Monitoring and development
We monitor data quality, the accuracy of AI outputs, and exception handling. We refine the rules and scale successful use cases.
From source data to controlled AI automation
We prepare the data, verify migration, and launch AI scenarios in a controlled environment. At each stage, we document the outcome and readiness criteria for the next step.
Data inventory
We identify data sources, owners, volumes, and structure, documenting reference data, business records, transaction history, and dependencies between objects.
Data quality profiling
We assess data completeness, formats, and freshness, identifying duplicates, gaps, inconsistencies, and broken relationships.
Cleansing and normalization
We remove duplicates, standardize values, agree on transformation rules, and map fields between systems.
Test and production migration
We run trial imports and verify completeness and referential integrity. After acceptance, we execute the agreed production migration plan.
AI use case configuration
We connect AI agents to prepared data and define instructions, constraints, and rules for delivering results to Creatio users.
Monitoring and development
We monitor data quality, the accuracy of AI outputs, and exception handling. We refine the rules and scale successful use cases.
Data migration and AI automation questions
Learn how we ensure data quality, preserve relationships between objects, control AI agent actions, and launch solutions in Creatio's production environment.
Before loading, we profile sources and define record matching criteria, including IDs, contact information, registration details, and other key fields. Merge and conflict rules are documented in the migration map, with ambiguous cases referred to responsible users for review.
For each object, we define source and target identifiers, dependencies, and loading order. Reference data and primary records are migrated first, followed by related documents and interaction history. We then verify record counts and referential integrity.
AI agents can classify requests, extract document data, score leads and opportunities, generate summaries, draft replies, and route tasks. Their actions are constrained by configured roles, instructions, and available business processes.
Approval is required for financial, contractual, and other critical operations, as well as low-confidence AI results or deviations from approved workflows. Users review the proposed action and make the final decision.
We track classification accuracy, corrections, exception rates, processing speed, and other scenario-specific metrics. Results are logged, and feedback informs instructions, constraints, and thresholds.
Before launch, we run trial migrations and prepare cutover. During the agreed window, we freeze source changes, migrate final data, reconcile results, and open user access. A rollback procedure covers critical discrepancies.
Data migration and AI automation questions
Learn how we ensure data quality, preserve relationships between objects, control AI agent actions, and launch solutions in Creatio's production environment.
Before loading, we profile sources and define record matching criteria, including IDs, contact information, registration details, and other key fields. Merge and conflict rules are documented in the migration map, with ambiguous cases referred to responsible users for review.
For each object, we define source and target identifiers, dependencies, and loading order. Reference data and primary records are migrated first, followed by related documents and interaction history. We then verify record counts and referential integrity.
AI agents can classify requests, extract document data, score leads and opportunities, generate summaries, draft replies, and route tasks. Their actions are constrained by configured roles, instructions, and available business processes.
Approval is required for financial, contractual, and other critical operations, as well as low-confidence AI results or deviations from approved workflows. Users review the proposed action and make the final decision.
We track classification accuracy, corrections, exception rates, processing speed, and other scenario-specific metrics. Results are logged, and feedback informs instructions, constraints, and thresholds.
Before launch, we run trial migrations and prepare cutover. During the agreed window, we freeze source changes, migrate final data, reconcile results, and open user access. A rollback procedure covers critical discrepancies.