Build Generative AI That Works for Your Business
Grawlix develops custom Generative AI solutions, LLM applications, RAG systems, enterprise AI assistants, AI agents and intelligent workflows that connect artificial intelligence with your business knowledge, applications, data and operations.
What Is Generative AI Development?
Generative AI development is the process of building software applications that use generative artificial intelligence models to create, summarize, retrieve, transform or interact with information. Solutions can include AI assistants, enterprise knowledge systems, RAG applications, AI agents, content intelligence, document processing and Generative AI features integrated into existing software. Grawlix develops these solutions around specific business requirements, data and workflows.
Turn Generative AI Into Practical Business Software
Grawlix helps businesses move beyond generic AI tools by building Generative AI applications around their knowledge, workflows, products, customers and technology environment.
Custom Generative AI Development
Purpose-built Generative AI applications designed around specific business problems, workflows, users and data.
Enterprise AI Assistants
Develop AI assistants that help teams interact with approved business knowledge, documents, applications and workflows.
AI Agent Development
Build intelligent agents that can interpret objectives, reason through tasks and interact with approved tools, APIs and business systems.
RAG Development
Build Retrieval-Augmented Generation systems that combine LLMs with relevant business knowledge for more contextual and grounded AI experiences.
LLM Application Development
Develop applications using suitable large language models with prompts, retrieval, business rules, integrations and application-specific interfaces.
Document Intelligence
Use Generative AI to help summarize, classify, extract, compare and interact with suitable business documents.
Generative AI Analytics
Create conversational experiences that make complex business information easier to explore and understand.
GenAI Integration
Integrate Generative AI into existing SaaS products, web applications, mobile apps, CRM, ERP and internal business platforms.
Generative AI Automation
Combine GenAI with APIs, software and workflows to support repetitive knowledge work and suitable operational tasks.
Connect AI With Your Business Knowledge
A generic language model does not automatically understand your private business information. Retrieval-Augmented Generation can retrieve relevant information from approved knowledge sources and provide that context to the model when generating an answer.
The architecture can combine documents, databases, vector search, language models, business rules and application interfaces.
Imagine an AI Assistant That Knows Your Business Knowledge
For example, a business could build an internal Generative AI assistant connected to approved policies, SOPs, project documents, knowledge articles and other suitable information.
Instead of searching manually across multiple documents, employees could ask a question and receive a contextual response based on retrieved company information.
Where Generative AI Can Create Business Value
The right Generative AI use case depends on your workflows, information, users, risk requirements and existing technology.
Customer Support AI
Help teams retrieve relevant information and prepare contextual customer responses.
Enterprise Knowledge Search
Make internal knowledge easier to discover through conversational interaction.
Document Summarization
Generate useful summaries from suitable long-form documents and business information.
Sales Assistance
Support research, proposal preparation and access to relevant sales knowledge.
HR Knowledge Assistant
Help employees find approved policies, procedures and internal HR information.
Developer Assistance
Create suitable AI-powered experiences around technical documentation and development workflows.
Content Intelligence
Assist with content research, transformation, classification and controlled generation.
AI Product Features
Add Generative AI capabilities directly to existing SaaS platforms and digital products.
Contract & Document Review
Assist users in retrieving and comparing relevant information from approved documents.
Research Assistance
Help teams organize, summarize and interact with large collections of relevant information.
Workflow Automation
Combine generated outputs with APIs and business processes to support suitable repetitive tasks.
Conversational Analytics
Create natural-language experiences for exploring appropriate operational or analytical information.
Build With the Right AI Model
Model selection should depend on the application, required quality, privacy, latency, deployment approach, integrations and commercial requirements rather than relying on a single provider for every use case.
From Business Challenge to Generative AI Application
A structured development process helps ensure the solution is designed around business requirements rather than simply adding AI for the sake of AI.
Discover
Define users, business problems, workflows and expected outcomes.
Assess
Review knowledge sources, data, integrations and feasibility.
Architect
Design the model, RAG, data, application and integration architecture.
Develop
Build prompts, retrieval, workflows, APIs and user experiences.
Evaluate
Test relevance, output quality, functionality and appropriate controls.
Deploy
Launch, monitor and continuously improve the GenAI application.
Technology for Production GenAI Applications
Depending on the solution, Generative AI development can combine models, orchestration frameworks, vector search, application development, APIs and cloud infrastructure.
Generative AI Across Different Industries
We design Generative AI solutions around industry workflows, business information, users and operational requirements.
Healthcare
Knowledge assistants, document intelligence and suitable AI-powered healthcare technology workflows.
Banking & Finance
AI-assisted document workflows, knowledge systems, customer operations and financial technology applications.
eCommerce & Retail
Shopping assistance, product intelligence, conversational search and commerce content applications.
SaaS & Technology
Embed Generative AI, assistants, agents and intelligent knowledge features directly into software products.
Logistics & Supply Chain
Operational knowledge, document assistance and Generative AI-enabled supply-chain workflows.
Education & eLearning
Learning assistants, educational knowledge systems and AI-powered content experiences.
Real Estate
Property assistance, document intelligence, lead experiences and conversational property search.
Manufacturing
Knowledge retrieval, SOP assistance, technical documentation and intelligent operational workflows.
Build GenAI as a Business Application
A production Generative AI solution needs more than an API call. It can require application development, retrieval, databases, integrations, access controls, cloud infrastructure, evaluation and an experience people can actually use.
Grawlix combines AI engineering with web, mobile, SaaS, software, API and cloud development to build complete Generative AI solutions.
Complete Generative AI Engineering
From identifying the use case to integrating AI into a working digital product.
Generative AI Development Questions Answered
Clear answers about Generative AI development, LLMs, RAG systems, AI agents and enterprise GenAI applications.
What is Generative AI development?
Generative AI development is the process of creating software applications that use generative models to generate, summarize, retrieve, transform or interact with information. Applications can include AI assistants, RAG systems, AI agents, document intelligence and Generative AI features within existing software.
What does a Generative AI development company do?
A Generative AI development company helps businesses design, develop, integrate and deploy applications powered by generative models. This can include model integration, RAG architecture, AI assistants, agents, vector search, application development, APIs and cloud deployment.
What Generative AI services does Grawlix provide?
Grawlix provides custom Generative AI development, LLM application development, RAG development, enterprise AI assistants, AI agents, document intelligence, Generative AI automation and integration with existing business applications.
What is an LLM?
A large language model, or LLM, is an AI model trained to process and generate language. LLMs can be used as part of applications for conversational interfaces, summarization, information transformation, retrieval-assisted experiences and other language-based tasks.
What is RAG in Generative AI?
Retrieval-Augmented Generation combines information retrieval with generative AI. Relevant information is retrieved from an approved source and provided to the language model as context for generating a response.
Why use RAG instead of only an LLM?
RAG can be useful when an application needs to work with specific or changing knowledge that is not reliably available from a model alone. The suitability of RAG depends on the use case, data and application requirements.
What is a Generative AI agent?
A Generative AI agent is an AI-powered software system that can interpret objectives, reason through steps and interact with approved tools or applications. The appropriate level of autonomy depends on the business process and required controls.
Can Generative AI use our company documents?
Yes, depending on the architecture and permissions. A solution can use approved documents and knowledge sources through methods such as retrieval and controlled application integrations.
Can Generative AI integrate with existing software?
Yes. Generative AI applications can integrate with suitable websites, mobile apps, SaaS products, CRM systems, ERP platforms, databases, APIs and internal software.
Can Grawlix build an enterprise AI assistant?
Yes. Grawlix can develop AI assistant applications that interact with approved organizational knowledge, documents, APIs and business workflows according to the application's requirements.
Can Generative AI be added to an existing SaaS product?
Yes. Generative AI features can be integrated into existing SaaS applications through APIs, application services, retrieval systems and appropriate user interfaces.
Which Generative AI model should my business use?
The right model depends on required output quality, use case, privacy, latency, cost, deployment approach, context requirements and integration needs. The model should be selected after understanding the application rather than choosing solely based on popularity.
How long does a Generative AI project take?
The timeline depends on the scope, integrations, knowledge sources, user experience, evaluation requirements and deployment environment. A focused proof of concept can be much smaller than a production enterprise GenAI platform.
Is Generative AI the same as traditional machine learning?
No. Generative AI focuses on models capable of generating new outputs such as text, images or code. Machine learning is a broader field that also includes prediction, classification, forecasting and other approaches.
How do I start a Generative AI project?
Start by identifying a specific business problem or workflow, the users involved, available knowledge or data, required integrations and the outcome the application should improve. The technology architecture can then be designed around those requirements.
Ready to Turn Generative AI Into a Real Business Application?
Talk to Grawlix about Generative AI development, LLM applications, RAG systems, AI agents, enterprise AI assistants and integrating GenAI into your existing software.
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