When most people hear AI agent, they picture a generic chatbot—one that can give decent general answers but struggles the moment the conversation requires real context, domain knowledge, or accuracy. That’s the limitation of traditional “ChatGPT wrapper” tools: they pass your question to a model and hope for the best.
The Core Design
Our entire platform is engineered around one idea:
AI should understand your business with the same depth and clarity as your best-trained human agent.
The heart of how we deliver on that promise—at scale and at speed—is our proprietary vector database infrastructure.
Vector DB Architecture
A vector database is a specialized data system designed to store information in a mathematical form that AI models can understand. Instead of storing documents as plain text, vector databases convert them into numerical “embeddings.” These embeddings represent semantic meaning:
what concepts are discussed
how ideas relate
which sentences are contextually similar
what information matters for answering a question
This lets AI find the right information instantly—not by keyword matching, but by meaning.
Think of it like giving your AI agent a supercharged memory.
Instead of flipping through documents or scanning text, it can access the exact piece of knowledge it needs in milliseconds.
Grounding LLM in Truth
Large language models (LLMs) like ChatGPT are powerful—but they do not know your business. Without contextual grounding, they:
Hallucinate answers
Invent policies or pricing
Forget conversation history
Provide vague or generic responses
Make compliance-risking mistakes
Contradict your internal documentation
This is why most “AI agents” feel unreliable.
Grounding changes everything.
Teli AI’s engine is built around ultra-fast context injection. Each message from your customer is processed through a pipeline designed for accuracy, memory, and speed.
1. Your Documents Become AI-Friendly Memory
When you upload PDFs, SOPs, CRM exports, training manuals, pricing sheets, pitch decks, or compliance documents, Teli AI converts every paragraph into numerical vectors. This turns your content into a searchable, AI-ready knowledge base.
2. Every Message Triggers Instant Semantic Search
When a customer sends a message or asks a question, the AI agent does not immediately respond. Instead, Teli AI:
Analyzes the user’s intent
Performs semantic search across thousands of document vectors
Retrieves the exact pieces of relevant context
Injects them into the model as grounding information
This ensures the AI is always pulling from reality, not imagination.
3. Ranking, Confidence Scoring, and Relevancy Filtering
Not all retrieved context is useful.
Teli’s system automatically:
Scores each chunk
Removes low-confidence matches
Ranks passages
Selects only the highest quality grounding material
Your agent only speaks from the most accurate, relevant information.
4. Response Generation in Under 600ms
Despite referencing enormous document sets, Teli AI remains exceptionally fast.
Below is a visualization of response time distribution across hundreds of real agent interactions:
Results
For businesses that use AI to speak with customers, accuracy is not optional.
Grounding ensures:
Correct pricing every time
No hallucinated claims
Consistent messaging across teams
Strong compliance alignment
Reliable long-form memory
Zero context drift
Fewer support escalations
Teli AI agents behave like trained employees—because they are trained on your real internal knowledge.
