What is the difference between an edge LLM and a cloud LLM?

A cloud LLM (such as ChatGPT or Claude accessed via API) processes your data on the provider's servers. An edge LLM runs on hardware you control, so data is processed locally and never transmitted to a third party.

Is edge LLM analysis less capable than cloud analysis?

Edge models are smaller than frontier cloud models, but for structured data analysis, summarization, and question answering over your own datasets, well-tuned edge models deliver strong results. The trade-off buys you something cloud models cannot offer at any price: your data never leaves.

Do we need special hardware to run Letalk?

Letalk is built on the same edge-optimized model deployment approach Knovik uses across its AI & Automation services, so it can run on modern on-premise servers or capable local hardware without requiring specialized AI infrastructure.

Edge LLM Data Analysis

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Letalk

Privately talk to your data. No cloud LLM required.

Letalk lets organizations talk to their data privately, without a cloud LLM. It is a data analysis product built on edge LLM technology: the language model runs locally, on your own hardware, so sensitive datasets are analyzed in natural language without a single record leaving your environment.

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Why It Exists

An edge LLM is a language model that runs locally, on a laptop, workstation, or on-premise server, instead of in a vendor's cloud. For data analysis, this changes the fundamental privacy equation: instead of moving your data to the AI, you move the AI to your data. Cloud LLMs are powerful, but every prompt sent to one is a data transfer to a third party. For regulated, confidential, or competitively sensitive datasets, that transfer is often the single blocker preventing an organization from using AI at all. Letalk exists to remove that blocker: ask questions of spreadsheets, databases, reports, and documents the way you would ask an analyst, and get an explained answer back, all inside your perimeter.

Key Features

What Letalk delivers

Edge-based LLM deployment, no cloud API calls

Natural language queries over spreadsheets, databases, and documents

Explained answers, not just raw output, with the reasoning shown

Connects to your existing data sources, read locally

How It Works

From question to answer, on your hardware

Connect your data

Spreadsheets, databases, and document sets, all read locally.

Ask in plain language

Letalk translates your question into queries against your data.

Get explained answers

Results come back with the reasoning, on your hardware, with nothing transmitted outside your environment.

Use Cases

Who needs this, and why

Healthcare and patient data

Clinical operations teams can ask "which readmission patterns appear in last quarter's discharge data" without any patient record leaving the hospital network, shrinking the compliance review from a cross-border data transfer assessment to an internal software approval.

Legal and privileged documents

Law firms and in-house legal teams can summarize case files, extract obligations from contracts, and query discovery documents entirely on firm-controlled hardware, keeping the privilege boundary intact because the documents never cross it.

Financial services and regulated data

Analysts can interrogate transaction data, loan books, and customer portfolios in natural language while the data stays inside the institution's own infrastructure, satisfying both the regulator and the internal risk committee.

Government, defense, and air-gapped environments

In classified or air-gapped networks with no internet connectivity, an edge LLM is the only way to bring natural-language data analysis in at all: the model, the data, and the analysis all live inside the secure enclave.

HR, payroll, and employee data

HR teams can ask "show attrition patterns by tenure band" against real employee data, without exposing a single personnel record to an external processor, a request their own DPO would otherwise block.

Manufacturing, R&D, and trade secrets

Engineers get conversational access to production and experiment data while product formulas, process parameters, and yield data stay under the organization's exclusive control.

Cross-border operations and data residency

When data collected in one jurisdiction cannot be processed in another, edge deployment sidesteps the problem entirely: if the data never leaves the country, the office, or the device, residency compliance is automatic.