AI agents designed for your data, tools, and workflows
NovCleda builds grounded AI agents that do far more than converse. Our autonomous and semi-autonomous agents connect to your internal knowledge bases, call business APIs, respect enterprise permissions, and hand off to human specialists when needed.
Why generic chatbots fail vs. How NovCleda AI Agents work
Traditional chatbots only produce text responses. Our AI agents ground their answers in live data, execute real API tools, and obey security permissions.
| Capability Aspect | Generic Chatbot ✕ | NovCleda Grounded AI Agent ✓ |
|---|---|---|
| Knowledge Base Eliminates hallucinations and ensures 100% accurate, up-to-date responses. | Static trained model weights with outdated knowledge. | Live RAG grounding connected to your live vector databases, Notion, and APIs. |
| System Action & Tool Use Transforms conversations into actual automated operational output. | Text-only conversations; cannot perform real work. | Calls REST APIs, schedules appointments, updates CRMs, and triggers webhooks. |
| Enterprise Permissions Prevents unauthorized employees or customers from viewing sensitive data. | No user context; gives identical answers to all users. | Enforces Role-Based Access Control (RBAC) per logged-in user session. |
| Human Escalation Guarantees a zero-frustration fallback whenever complex edge cases arise. | Gets stuck in loops or drops conversations silently. | Seamlessly transfers full chat transcript & context to human agents in Slack/Zendesk. |
Experience Grounded Agent Execution
Explore our interactive HTML/CSS product interfaces demonstrating real-time RAG retrieval, tool calling, and human agent takeover.
Grounded AI Agent in Action
Real product UI demonstrating RAG grounding, tool invocation, and human escalation.
Your order #ORD-8821 is currently in transit with FedEx and estimated to arrive tomorrow by 3:00 PM.
I have checked our onboarding team's calendar. Would tomorrow at 4:30 PM work for your specialist call?
If the user requests a custom refund or expresses frustration, the agent transfers the active session to a human agent with the complete order history attached.
7 AI Agent Solutions Built for Business
From Tier-1 customer support to legal document Q&A and operational workflow automation.
Customer Support Assistant
Resolves common customer inquiries, looks up order statuses via API, guides troubleshooting, and escalates complex issues to human support agents.
Sales & Inbound Assistant
Engages website visitors, answers product questions using verified documentation, qualifies buyer intent, and books meetings on sales calendars.
Internal Knowledge Assistant
Indexes internal wikis, Slack channels, Notion docs, and code repos to give employees immediate answers with exact source document citations.
Document Q&A Agent
Allows teams to upload multi-page contracts, legal briefs, medical papers, or technical manuals and query specific clauses with page references.
Employee & HR Assistant
Assists staff with PTO requests, benefits inquiries, IT password resets, hardware requests, and policy guidance through Slack or Teams.
Operational & Workflow Agent
Monitors system events, runs diagnostic queries, generates daily operational summaries, and executes routine system maintenance tasks.
Appointment & Request Assistant
Guides clients through multi-step intake forms, verifies availability against live calendar APIs, sends confirmation reminders, and manages reschedules.
6-Layer Agent Architecture Concept
Every NovCleda agent is constructed around 6 modular layers to ensure security, accuracy, and enterprise scalability.
How NovCleda AI Agents Are Built
Explore the 6 core components powering grounded, secure, and tool-enabled enterprise AI agents.
1. User Query & Session
Multi-Channel Interface
2. AI Agent Reasoning Engine
LLM & Intent Classifier
3. Knowledge & Data (RAG)
Vector Store Grounding
4. Business Rules & Permissions
RBAC & Security Guardrails
5. Tools & API Execution
Function Calling & Webhooks
6. Human Escalation Checkpoint
Seamless Agent Handoff
2. AI Agent Reasoning Engine
Decomposes complex query into actionable steps, evaluates prompt constraints, and selects necessary tools.
Built on 6 Core Engineering Pillars
How we guarantee data privacy, accuracy, permission control, and continuous evaluation.
RAG & Knowledge Grounding
We connect your AI agents to vector databases (pgvector, Pinecone) using hybrid semantic search. Agents cite exact documents and never make up answers.
Enterprise Permissions & RBAC
Agents strictly respect user identity, enforcing document permission levels so employees or customers only see data they are authorized to access.
Tool Use & API Execution
Equipped with function calling capabilities, agents execute REST/GraphQL endpoints, query SQL databases, and trigger n8n webhooks securely.
Human Handoff & Governance
When confidence is low or a user requests a human, the agent instantly transfers the complete conversation history to your support team in Slack, Teams, or Zendesk.
Analytics & Evaluation Pipeline
We track hallucination scores, response latencies, user satisfaction ratings, and token costs in real-time to continuously optimize prompts and models.
Enterprise Security & Privacy
Your proprietary company data is never used to train public LLM models. Options to deploy on private AWS/GCP cloud or self-hosted models.
Structured 4-Phase Agent Delivery
From initial data indexing to live guardrailed agent deployment.
Data Audit & Agent Blueprint
Map target use cases, catalog knowledge sources, define API tool schemas, and establish permission boundaries.
RAG Pipeline & Tool Integration
Set up vector embeddings database, connect REST APIs, implement function calling logic, and build custom prompt chains.
Guardrails & Human Handoff Testing
Stress-test hallucination resistance, test permission enforcement, configure Slack/Zendesk human escalation, and benchmark latency.
Deployment & Continuous Evaluation
Deploy to production website/app, configure analytics dashboards, monitor token usage, and continuously tune accuracy.
AI Agent Development FAQs
Clear answers regarding data privacy, hallucinations, integrations, and deployment times.
We use Retrieval-Augmented Generation (RAG) combined with strict system guardrails. The agent is restricted to answering exclusively using verified data retrieved from your vector database. If the answer is not in your documents, it is configured to state that clearly or hand off to a human.
A standard chatbot only generates text based on broad training data. A NovCleda AI Agent connects directly to your private company data, understands your business rules, enforces user permissions, and executes real actions via APIs (such as booking appointments or updating CRMs).
No. We utilize enterprise API agreements (OpenAI Enterprise, Anthropic, Google Cloud Vertex AI) that explicitly guarantee zero data retention and zero model training on your inputs. We also offer fully self-hosted open-source model options (Llama 3).
If the agent detects low confidence, a frustrated user, or a specific user request for a human, it automatically pauses, formats a summary of the conversation, and routes the full transcript to your team's live chat (Slack, Microsoft Teams, Zendesk, or HubSpot).
Yes. Our agents use standard REST/GraphQL APIs and webhooks to integrate with Salesforce, HubSpot, Zendesk, Shopify, Notion, Google Workspace, PostgreSQL databases, and custom backends.
A focused enterprise knowledge or support agent can typically be prototyped within 1 to 2 weeks and fully deployed with guardrails in 3 to 4 weeks.
Ready to empower your team with intelligent AI agents?
Discuss your company data, tools, and workflows with NovCleda. We'll design a grounded AI agent architecture tailored specifically to your operational goals.