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- Overload due to repetitive tasks
- Delays that slow down operations
- Simple queries that saturate the channel
| | Support and internal operations | An agent that understands natural language, grants access to the company systems, and replies in real time | - 24/7 availability
- Fewer errors
- Increased productivity
- Time and cost savings
- Reduced repetitive queries
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- Inefficiency in supervision and anomaly detection
- Manual control processes that are prone to errors.
| | Real-time visual detection and analysis | A system that detects objects, events, or anomalies in real-time video streams | - Increased security and control
- Issuing immediate alerts for critical events
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- Delays due to manual reviews
- Bugs found in production
- Lack of code standardization
| | Real-time code quality and security control. | AI agent that analyzes repositories, detects bugs and vulnerabilities, and suggests improvements before release. | - 30% less rework
- Improved security and stability
- Faster time-to–market
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- Financial losses
- Inefficiency in budget allocation and resource management
| | | A predictive model that generates forecasts of future demands or events based on historical data. | - Optimization of decision-making and resource management.
- Increased profitability
- More precise strategic planning.
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- Manual or inefficient processes for credit approval.
- Loss of time and resources
| | Default probability scoring | A model that assesses the probability or risk and generates a score for real-time decision–making | - Reducing financial and operational risk.
- Optimizing assessment and approval processes.
- Preventing future behaviour.
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- Poor personalization
- Loss of sales due to irrelevant suggestions
- Inefficiency in user retention.
| | Real-time recommendation engine | An engine that suggests products, content, or services based on the user's behaviour and preferences | - Improved user experience and engagement.
- Increased sales and conversions.
- Optimizing user retention.
- Increased agility in decision-making.
- Generating suggestions in milliseconds.
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- Legal and financial risks due to sensitive data.
- Regulatory compliance challenges.
- Manual anonymization processes that are slow and expensive.
- Vulnerabilities to data breaches.
| | | Automated pipelines that anonymize multiple data in multiple formats (PDFs, images, audio). | - Guaranteed regulatory compliance.
- Risk reduction.
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- Difficulty in maintaining consistent content production.
- Long production times.
| Content Generation and Summarization | Dynamic content creation. | A tool that drafts emails or blog posts, and summarizes PDF files, while maintaining the brand's tone. | - Brand consistency.
- Personalization.
- Increased productivity.
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- Slow and manual processes.
- High costs
- Human errors
| Scanned Document Processing | Data extraction automation | An automated pipeline that digitizes documents, extracts key data, and structures it into a specific format | - Time and cost savings.
- Error reduction.
- Increased operational efficiency.
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- Complex BI tools that don’t support natural language
- Difficulty integrating multiple sources
- Limited, slow data access that is dependent on technical experts
| | | A BI chat connected to multiple data sources that allows you to ask questions in natural language and receive answers as tables or charts. | - Simplified data access.
- Increased security
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- Brand inconsistency in image creation.
- Lack of control over visual assets
- Absence of personalized presets
| | Branded visual content creation. | A tool that generates branded images, with moderation and asset control. | - Increased consistency and personalization
- Centralized management of visual assets
- Increased speed in content creation.
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- Slow and manual identity verification processes
- High costs
- Lack of regulatory compliance
| Facial Recognition and Proof of Life | | An SDK to verify identity with high precision and regulatory compliance. | - Security and regulatory compliance
- Operational cost reduction
- Streamlining client onboarding
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- Lack of data integration
- Poor personalization
- Low effectiveness
| | | A tool that identifies audiences, creates personalized content, and sends it through the most effective channel. | - Increased personalization and effectiveness in campaigns.
- Data integration for a unified strategy
- Communication channel optimization
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- Low precision in relevant data extraction.
- Limited personalization by industry and language.
| | Text analysis and processing | AN API that extracts entities with high precision, tailored to a specific domain. | - Precise data extraction
- Increased personalization
- Increased efficiency
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- Difficulty integrating in AWS-first environments
- Lack of control over the model lifecycle
- Incompatibility with custom landing zones
| | Model lifecycle management | A MLOps platform that integrates natively with AWS, enabling monitoring and full control. | - Native integration with the AWS environment
- Complete management of the model lifecycle
- Continuous monitoring of model drift
- Deployment and pipeline automation
- Rollback capability and full control over models
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- Generic tools that don’t adapt to specific formats
- Low precision in sensitive data extraction
| | Data extraction automation | A system that extracts data from forms with high precision, tailored to specific formats and standards. | - Increased precision and efficiency
- Time savings in record management
- Operational cost reduction
- Data centralization
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What problems does AI solve?
How can AI be used in business?
What AI solutions does Crombie offer?
