AI & Intelligent Systems | Agentic AI, Multi-Model Routing, RAG & Predictive Automation

Secure LLM Integrations for Real Enterprise Workflows

Enterprise LLM Integrations are about more than calling an API. It’s about embedding models like GPT, Claude, Gemini, LLaMA and open-source LLMs directly into your business systems—securely, reliably, and with full control over data, behavior, and how each request is routed to the right model or agent.

At Codefremics, we design and deploy LLM-powered capabilities into ERPs, CRMs, HR systems, support desks, data warehouses, and custom apps. We implement LLM routing and multi-agent orchestration—so different models and agents handle different tasks based on context, cost and sensitivity—while keeping a strong focus on governance, observability, guardrails, and performance so your AI layer is production-ready, not just experimental.

What We Build With Enterprise LLM Integrations

We combine LLM orchestration frameworks, secure connectors, RAG pipelines, and LLM routing to make AI a first-class citizen inside your enterprise architecture—backed by logging, monitoring, and policy controls. Your system can automatically decide which model or agent should handle each request.

LLM Integration Architecture & Routing

Design of API gateways, orchestration layers, and routing logic that decide which model or agent handles each prompt—based on use case, sensitivity, latency, and cost—so LLMs plug cleanly into your existing backend and microservices.

Embedded LLM Experiences

Add chat, summarization, drafting, and recommendation features directly inside your web apps, mobile apps, and internal tools—with the right agent being called behind the scenes.

RAG & Enterprise Data Connectors

Build Retrieval-Augmented Generation (RAG) over your documents, data warehouses, ticket histories, and logs—without exposing raw data externally. The router decides when to call RAG versus a pure reasoning model.

Tool Use & Function Calling

Enable LLMs to call your APIs, run actions, and trigger workflows safely through structured function calling and role-aware permissions—under the control of an orchestration layer.

Private & Multi-Model Deployments

Architect solutions that mix cloud LLMs, on-prem models, and open-source models, with routing based on cost, sensitivity, jurisdiction, or use case. Sensitive prompts can be routed to private models, while others use cheaper public APIs.

Observability & Guardrails

Logging, prompt and response monitoring, safety filters, and policy checks so every interaction—and every routing decision—is auditable and policy-aligned.

Enterprise LLM Integration Use Cases

We bring LLM capabilities into the systems your teams already rely on, across operations, finance, support, product, and leadership—with routing and multi-agent patterns ensuring the right “expert” is used for each task.

LLM-Powered CRMs

Summarize accounts, generate call notes, suggest next actions, and draft emails inside your CRM (HubSpot, Salesforce, custom tools)—with separate agents for sales, support and renewals.

Support & Ticketing Systems

Integrate LLMs with Zendesk, Freshdesk, custom helpdesks to summarize cases, propose replies, and tag issues automatically—with routing between FAQ, escalation and quality-check agents.

Document & Knowledge Systems

Add “ask anything” search over policies, contracts, and SOPs by integrating LLMs with SharePoint, Google Drive, or private data lakes, and route queries to the right domain-specific knowledge agent.

Back-Office & ERP Workflows

Integrate LLMs into your ERP, finance, and HR systems to draft memos, summarize reports, auto-generate documentation, and route tasks between finance, HR and ops agents.

Executive Dashboards & Briefings

Embed LLMs in BI dashboards to turn complex charts and PDFs into concise narratives, risks, and recommended actions for leadership—powered by routing between analytics and summarization agents.

Multi-Agent Assistants

Deploy multi-bot assistants where a routing layer decides whether a query goes to a policy bot, data bot, coding bot, or knowledge bot, and then returns a single, coherent response to the user.

Enterprise LLM Integrations