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Generative AI & LLM
Generative AI & LLM Development Services
Build LLM-powered applications, AI search systems, enterprise chatbots, and intelligent product experiences that turn business data into useful, accessible knowledge.
Overview
What Are Generative AI & LLM Solutions?
Generative AI and large language model solutions help businesses search, summarize, generate, analyze, and transform information using artificial intelligence.
These systems can work with your approved documents, databases, knowledge bases, and existing software to deliver faster access to information and more intelligent user experiences.
Grayphite designs and develops production-ready LLM applications for internal teams, customer-facing products, and enterprise workflows.
What LLM solutions can do
- Help teams find relevant answers across documents, databases, and internal systems.
- Create, summarize, rewrite, classify, and extract information from text-based content.
- Process large volumes of information and surface useful insights faster.
- Add AI search, chat, recommendations, and intelligent content experiences to existing software.
Business challenges
Business Challenges Generative AI & LLM Can Help Solve
Generative AI and LLM helps businesses reduce the time spent searching, writing, processing, and analyzing information across teams and systems.
Slow Content Workflows
Accelerate drafting, editing, summarization, and content transformation tasks.
Manual Document Review
Extract, classify, summarize, and analyze information from large volumes of text.
Repetitive Customer Queries
Answer common questions faster with context-aware AI chatbots and assistants.
Limited AI Capabilities in Existing Products
Add intelligent search, recommendations, and conversational experiences to your software.
Difficulty Moving AI Into Production
Build reliable LLM applications with the right architecture, integrations, testing, and guardrails.
WHAT WE BUILD
Generative AI & LLM Solutions We Build
We design and develop production-ready LLM solutions that help businesses search knowledge, generate content, automate language-heavy tasks, and add intelligent experiences to digital products.
LLM Development
Build custom large language model applications for knowledge access, document analysis, content generation, summarization, and specialized business workflows.
ViewGPT Integrations
Add GPT-powered features to your existing software, including intelligent search, content generation, document processing, customer support, and in-product AI assistants.
ViewClaude & OpenAI Integrations
Integrate Claude and OpenAI models into your products and workflows using secure APIs, prompt engineering, model routing, guardrails, and evaluation pipelines.
ViewAI Search Systems
Create intelligent search experiences that retrieve relevant answers from business documents, databases, knowledge bases, and connected enterprise systems.
ViewEnterprise Chatbots
Develop secure, context-aware AI chatbots for customers and internal teams, with business-data grounding, system integrations, and human handoff when needed.
ViewMulti-Agent Systems
Build coordinated AI systems in which specialized agents collaborate, share context, and complete complex tasks across multiple workflows and business tools.
ViewIndustry applications
Generative AI & LLM Solutions by Industry
The right language intelligence, tuned to your sector.
HealthTech
Generative AI and LLM helps healthcare businesses improve knowledge access, reduce administrative workload, and support more efficient patient and staff experiences.
- Medical documentation search
- Patient support chatbots
- Clinical content summarization
- Healthcare knowledge assistants
- Administrative document processing
FinTech & Financial Services
Generative AI helps financial organizations analyze documents, improve information access, and streamline customer and compliance-related workflows.
- Financial document analysis
- Compliance policy search
- KYC onboarding document review
- Analyst research assistants
- Customer support chatbots
Ecommerce
Generative AI helps ecommerce businesses improve product discovery, customer support, and content operations across digital channels.
- Product discovery assistants
- Customer support chatbots
- Product catalog enrichment
- Review summarization
- Product description generation
AdTech
Generative AI helps advertising and marketing teams accelerate campaign planning, improve reporting, and streamline content workflows.
- Campaign brief generation
- Performance summary generation
- Creative ideation assistants
- Audience insight copilots
- Marketing knowledge search
EdTech
Generative AI helps education businesses improve learning experiences, simplify content access, and reduce repetitive content-related work.
- Learning support chatbots
- Course content generation
- Student knowledge search
- Assessment feedback support
- Instructor copilots
Consulting
Generative AI helps consulting firms improve research, retrieve internal knowledge, and create client-facing deliverables more efficiently.
- Proposal drafting support
- Research synthesis
- Report generation
- Document summarization
- Internal knowledge search
Technology ecosystem
Technologies We Use to Build Generative AI & LLM Solutions
Model-flexible, integration-ready, and designed for production.
LLM Providers
OpenAI
Anthropic Claude
Google Gemini
Meta Llama
MistralAI Frameworks
LangChain
LlamaIndex
LangGraph
HaystackVector Databases & Search
Pinecone
Weaviate
Qdrant
PostgreSQL with pgvector
ElasticsearchPowered byGrayphiteGenAI Stack
Cloud & Deployment
AWS
Azure
Google Cloud
Docker
KubernetesEnterprise Integrations
Salesforce
HubSpot
Slack
Microsoft TeamsSharePointApplication Engineering
Python
FastAPI
Node.js
React
Next.jsAI Project Estimator
Estimate Your Generative AI & LLM Project
Answer a few questions about your use case, data sources, integrations, security needs, and product goals. Our estimator will help you identify the likely scope, complexity, and recommended starting point for your LLM project.
- Identify the most suitable model, retrieval, or integration approach.
- Understand the likely size and complexity of your project.
- Receive a clear recommendation for moving forward.
Our process
Our Generative AI and LLM Development Process
From use case to production-ready LLM solution.
Discovery & Strategy
- Business goals and use-case mapping
- Workflow assessment
- Knowledge source review
- Success criteria definition
Solution Blueprint
- Model selection strategy
- RAG and application architecture
- Integration planning
- Security and governance requirements
Proof of Concept
- Functional LLM prototype
- Prompt and retrieval evaluation
- Feasibility validation
- Stakeholder review
Production Development
- Production-ready LLM application
- Secure system integrations
- Guardrails and quality testing
- Deployment and launch
Scale & Optimize
- Performance monitoring
- Accuracy improvements
- Cost and latency optimization
- Continuous enhancements
Case studies
Real systems Measured outcomes
Featured case study
AI-Powered Website & Marketing Automation Platform
Read the full case study
AI-Powered Google Ads Performance Evaluation Platform
View Case Study
SEM Growth
SEM Growth Transforms Marketing Attribution into Revenue Intelligence
View Case Study
EFC Scales Multi-Product Engineering with Embedded Teams
View Case Study
Polaris Builds AI-Powered Legal Collaboration with RAG-Driven Intelligence
View Case Study FAQ
Frequently Asked Questions
What are Generative AI and LLM solutions?+
Generative AI and LLM solutions are software applications powered by large language models. They can generate content, answer questions, summarize information, analyze documents, search business knowledge, and support digital workflows.
What types of Generative AI solutions can Grayphite build?+
Grayphite builds custom LLM applications, GPT integrations, Claude and OpenAI integrations, AI search systems, enterprise chatbots, and multi-agent systems tailored to specific business needs.
What is LLM development?+
LLM development is the process of designing and building applications powered by large language models. These applications can use business data, connect with software tools, and support use cases such as search, summarization, content generation, and document analysis.
Can generative AI integrate with our existing software?+
Yes. Generative AI solutions can integrate with CRMs, ERPs, databases, internal tools, cloud platforms, communication systems, and third-party APIs.
What is a GPT integration?+
A GPT integration adds GPT-powered capabilities to an existing product or workflow. Common examples include AI search, content generation, document processing, customer support, summarization, and in-product assistants.
Can you integrate both Claude and OpenAI models?+
Yes. We can integrate Claude, OpenAI, and other leading language models into the same solution. The right model can be selected based on accuracy, speed, privacy, cost, and use-case requirements.
How do you choose the right LLM for a project?+
We evaluate the use case, data sensitivity, response quality, context requirements, speed, infrastructure, scalability, and cost before recommending a model or multi-model approach.
What is an AI search system?+
An AI search system helps users retrieve relevant information from documents, databases, knowledge bases, and connected business systems using natural-language queries.
How is AI search different from traditional search?+
Traditional search usually depends on keywords. AI search can understand user intent, retrieve relevant context, and generate more useful answers from approved knowledge sources.
What is an enterprise AI chatbot?+
An enterprise AI chatbot is a secure, business-focused conversational system that can answer questions using approved company data, integrate with internal tools, and escalate complex requests to human teams when needed.
Can an enterprise chatbot use our internal documents?+
Yes. Enterprise chatbots can work with approved documents, policies, knowledge bases, databases, and internal systems while respecting user permissions and access controls.
What is retrieval-augmented generation?+
Retrieval-augmented generation, or RAG, allows an LLM application to retrieve relevant information from approved sources before generating an answer. This helps improve accuracy, relevance, and traceability.
Should we use RAG, fine-tuning, or prompt engineering?+
The right approach depends on the use case. Prompt engineering improves instructions, RAG helps the system use approved business knowledge, and fine-tuning may be suitable for specialized behavior or repeated patterns.
What are multi-agent systems?+
Multi-agent systems use multiple specialized AI agents that collaborate, share context, and complete complex tasks across workflows, data sources, and software tools.
How do you improve the accuracy of LLM applications?+
We improve reliability through prompt design, retrieval architecture, structured outputs, evaluation workflows, guardrails, monitoring, testing, and human approval steps where appropriate.
How do you protect sensitive business data?+
We design solutions with secure integrations, access controls, data-handling policies, permission-based retrieval, monitoring, and deployment options aligned with your privacy and security requirements.
Can generative AI be added to an existing SaaS product?+
Yes. We can embed AI search, chat, summarization, document analysis, recommendations, and content-generation features into existing SaaS platforms and digital products.
How long does it take to build an LLM-powered application?+
Timelines depend on the use case, data sources, integrations, security requirements, and product complexity. A focused proof of concept may take a few weeks, while a production-ready enterprise solution usually requires a phased implementation.
How much does a generative AI or LLM project cost?+
The cost depends on project scope, model requirements, integrations, data preparation, infrastructure, security needs, and ongoing usage. We provide a tailored estimate after reviewing your goals and technical requirements.
How do I start a generative AI project with Grayphite?+
Start by sharing your use case, data sources, existing systems, and business goals. Our team will recommend the right LLM approach and define a practical roadmap for development.
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