How do you prevent the AI from making things up (hallucinating)?

We use Retrieval-Augmented Generation (RAG) to ground every AI response in verified source documents. The model can only answer from content it can cite. We also implement confidence thresholds: if the model isn't sure, it escalates to a human rather than guessing.

Can we build an internal knowledge bot on top of our existing documentation?

Yes. This is one of our most requested implementations. We index your Confluence, Notion, SharePoint, or PDF libraries into a vector database, then build a chat interface where employees get instant, cited answers from your own documentation.

What LLMs do you work with?

We're model-agnostic. We work with GPT-4, Claude, Gemini, Llama, and Mistral depending on your privacy requirements, latency needs, and budget. For maximum data privacy, we often recommend self-hosted Llama or Mistral in a private cloud.

Data & Analytics

Generative AI & NLP Business Solutions that Read Everything

Unlocking the power of LLMs to automate document analysis, accelerate content creation, and decode customer intent at a scale no human team can match.

Talk to an Expert

Start your project with us

Conversational Intelligence

Text is your biggest untapped data source. We use Generative AI and NLP to read through millions of emails, documents, and transcripts, automatically extracting insights, routing requests, and generating on-brand responses that used to require armies of analysts. Retrieval-augmented generation grounds every answer in your own verified documents, so the output is fast and scalable without drifting into the hallucinations that make generic models risky for enterprise work.

The Old Way

Text Blindness

The Intelegencia Way

LLM Powered

Manual Document Review

Instant Doc Summaries

Missed Customer Intent

Deep Intent Analysis

Slow Content Creation

Automated Content Gen

Inconsistent Branding

Brand-Voice Consistency

Information Overload

Zero-Latency Search

Retrieval-Augmented Generation (RAG)

We connect LLMs to your private company data, creating a custom AI that knows your products, policies, and history better than any generic model. RAG eliminates hallucinations by grounding every answer in verified source documents. A tuned vector database, semantic search, and secure document parsing keep responses both fast and citable, so employees and customers trust the answer because they can trace exactly where it came from.

Vector Database Setup

Semantic Search Optimization

Hallucination Control Guardrails

Fine-Tuning for Domain

Secure Document Parsing

Intelligent Document Processing

We build NLP pipelines that read contracts, invoices, support tickets, and research reports, extracting structured data, flagging anomalies, and routing exceptions to the right team. What takes humans hours takes our pipelines seconds. Layout-aware parsing, named-entity recognition, and clause-level extraction turn unstructured paperwork into clean database fields, while multi-language support means the same pipeline works across every region you operate in.

OCR + Layout-Aware Parsing

Named Entity Recognition (NER)

Contract Clause Extraction

Sentiment & Tone Analysis

Multi-Language Support

AI Content Generation at Scale

We build content workflows that use LLMs to generate product descriptions, marketing copy, email sequences, and internal documentation, all tuned to your brand voice, reviewed by built-in guardrails, and delivered through the tools your team already uses. Human-in-the-loop review queues and SEO-aware templates keep quality high at volume, so output scales from dozens to thousands of assets a week without the brand drifting or a person ever leaving their workflow.

Brand Voice Fine-Tuning

Multi-Format Content Templates

Human-in-the-Loop Review Queues

SEO-Aware Generation

Localization & Translation Workflows

The Language Stack

Gen-AI Units

Intent recognition, document summarization, content generation, and knowledge retrieval engines that unlock millions of unstructured text signals, turning them into actionable business intelligence.

Intent Engine

Knowing exactly what a customer wants from raw, unstructured text.

Summary Bot

Turning 100-page documents into 5 actionable bullet points instantly.

Content Forge

Generating high-quality, on-brand marketing copy and documentation at scale.

Knowledge Hub

A private ChatGPT built on your internal company documents and policies.

The Implementation

Our Gen-AI Flow

Safely deploying LLMs in the enterprise with the guardrails that make production deployments trustworthy.

Use-Case Audit

Finding the 3 text-heavy workflows that save the most time when automated.

Data Vectorization

Turning your documents into mathematical embeddings for semantic search.

Prompt Engineering

Designing the logic, constraints, and formatting rules for LLM responses.

Guardrail Setup

Ensuring the AI stays on-brand, factually grounded, and safe for enterprise use.

App Integration

Plugging the AI into your existing software via API, Slack, or embedded widget.

Measured Performance. Proven Growth.

Response Speed

Intent Accuracy

Content Output

Hallucination Rate

Frequently Asked Questions
About Generative AI & NLP Business Solutions

Here you will find answers to questions we get asked the most about our offerings.

We use private VPC deployments of LLMs: either self-hosted open-source models or enterprise tiers of GPT/Claude with data processing agreements. Your company data never trains the model or leaves your secure cloud environment.