AI Solutions for Companies | 100% Customizable

Implement AI solutions today and see results in less than 30 days

AI Agent

An AI-powered solution that performs real-time actions, accesses your company’s data, and engages in conversations aligned with your brand voice. It enables 24/7 support, reduces operational workload, and enhances customer experience.

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Computer Vision

AI that analyzes images and video in real time to detect objects, validate information, and trigger automated actions. It improves security, quality control, and operational efficiency by eliminating manual processes and generating insights that accelerate decision-making.

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Code Review Agent: Eagle AI

An AI agent that analyzes code in real time to identify bugs, vulnerabilities, and areas for improvement before deployment. It speeds up development and reduces rework by up to 30%.

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Why Implement Generative Artificial Intelligence?

74 %

of organizations are already seeing a ROI from their Generative AI projects.

86 %

of organizations using Generative AI report revenue growth.

84 %

of organizations are able to take Generative AI use case idea to production in under 6 months.

Boost your Business Results with our AI Solutions

Challenges	Use Case	Practical Case	Solution	Benefits
Overload due to repetitive tasks Delays that slow down operations Simple queries that saturate the channel	Conversational Agent	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
Inefficiency in supervision and anomaly detection Manual control processes that are prone to errors.	Computer Vision	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
Delays due to manual reviews Bugs found in production Lack of code standardization	Code Review Agent	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
Financial losses Inefficiency in budget allocation and resource management	Forecast	Inventory demand	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.
Manual or inefficient processes for credit approval. Loss of time and resources	Risk and Scoring	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.
Poor personalization Loss of sales due to irrelevant suggestions Inefficiency in user retention.	Recommendation Systems	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.
Legal and financial risks due to sensitive data. Regulatory compliance challenges. Manual anonymization processes that are slow and expensive. Vulnerabilities to data breaches.	Text Generation	Legal documents drafting	Automated pipelines that anonymize multiple data in multiple formats (PDFs, images, audio).	Guaranteed regulatory compliance. Risk reduction.
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.
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.
Complex BI tools that don’t support natural language Difficulty integrating multiple sources Limited, slow data access that is dependent on technical experts	Conversational BI	Corporative data query	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
Brand inconsistency in image creation. Lack of control over visual assets Absence of personalized presets	Generative Image	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.
Slow and manual identity verification processes High costs Lack of regulatory compliance	Facial Recognition and Proof of Life	User authentication	An SDK to verify identity with high precision and regulatory compliance.	Security and regulatory compliance Operational cost reduction Streamlining client onboarding
Lack of data integration Poor personalization Low effectiveness	Marketing Automation	Smart marketing campaign	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
Low precision in relevant data extraction. Limited personalization by industry and language.	Entity Extraction	Text analysis and processing	AN API that extracts entities with high precision, tailored to a specific domain.	Precise data extraction Increased personalization Increased efficiency
Difficulty integrating in AWS-first environments Lack of control over the model lifecycle Incompatibility with custom landing zones	MLOps Platform	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
Generic tools that don’t adapt to specific formats Low precision in sensitive data extraction	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

Frequently Asked Questions About AI Solutions

What problems does AI solve?

Artificial Intelligence enables the automation of repetitive tasks, reduces errors, and speeds up processes that once relied on manual work. It also enhances decision-making through predictive models and real-time data analysis. For many companies, AI eliminates operational bottlenecks and enables greater efficiency and scalability.

How can AI be used in business?

Companies are adopting generative AI to accelerate content creation and improve internal communication. They use predictive models to anticipate scenarios and make more accurate decisions. Computer vision is integrated to monitor operations, and intelligent agents are deployed to automate critical tasks.

What AI solutions does Crombie offer?

Crombie develops generative AI solutions such as AI Agents, Forecast, Computer Vision, and BI Chat, among others. It also offers Eagle AI, a Code Review Agent designed to optimize the software development lifecycle (SDLC). All of these solutions can be integrated rapidly and deliver measurable results in less than 30 days.

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