amber
amber_vs_langdock
Langdock alternative with deep integrations

Many companies are currently looking for GDPR-compliant alternatives to ChatGPT. The challenge of employees bringing private AI tools to the workplace and there being no control over who uploads what data and where is omnipresent. Langdock offers a simple alternative here – but quickly reaches its limits when companies want to take their own knowledge into account. If you want to get started quickly and value integrations with existing systems, you should definitely take a look at amber.

Quick comparison

amber

amber delivers consistently accurate answers quickly with its own semantic context layer, is easy to use and enterprise‑ready, and drives measurable impact in heterogeneous environments.

Langdock

Model-agnostic AI platform with superficial integrations and a multi-model API that is strongly modeled on ChatGPT. Langdock relies on users manually uploading data and keeping it up to date.

Technical approaches 
amber

• Uses its own semantic context layer with optimized AI retrieval to query a central index, providing accurate and consistent answers with fast runtimes even in complex IT landscapes.
•Integrates deeply with on‑premise and cloud systems and fully respects permissions for secure, compliant use across all data sources.
• Offers standard connectors and multi‑channel access for seamless embedding into existing workflows and applications.
• Produces higher answer quality through consistent context, reducing noise and improving relevance for end users.
• Delivers faster response times by avoiding third‑party lookups at search time and leveraging a central index.
• Establishes a robust decision basis for AI agents by enriching results with reliable, permission‑aware contextual knowledge.
• Increases measurable business value by accelerating information access, improving decision quality, and reducing follow‑ups.
• Remains simple to use for employees: ask a question and receive a precise, trustworthy answer across systems.
Scales across heterogeneous IT environments without adding operational complexity for teams.

Both

Both approaches allow actions in third-party systems.

Langdock

• Langdock relies on the native searches of connected systems, which means that the quality is limited by their constraints and a federated rather than semantically unified search.
• Langdock offers more superficial integrations (MCP-Approach and federated search approach) with a focus on model-agnostic chat interaction and without consistent permissions.

History of amber

amber was founded in Aachen in 2020 to make internal company knowledge quickly and easily accessible with AI. The challenges that amber solves are mostly along these lines:

  1. 1
    Grown IT infrastructures – IT infrastructures have grown over the years, with information scattered across drives, M365, Atlassian, DMS, or intranet
  2. 2
    Knowledge carriers leave the company – the “remaining” employees face challenges in quickly accessing internal knowledge
  3. 3
    Processes & products are becoming more complex – employees must keep track of ever-increasing amounts of data
  4. 4
    Employees use private AI solutions – Employees are aware of the challenges mentioned above, which is why they use private AI tools to become more efficient

While the fourth challenge only arose after the release of ChatGPT, we began addressing the first three challenges in 2020 with what is known as enterprise search. The initial goal was to build a kind of “internal Google” for the company. Amber’s focus was therefore initially on integrating a wide variety of software solutions. amber differs from solutions such as Langdock in that amber builds its own index and searches using its own AI logic, while Langdock relies on the search functions of SharePoint, drives, and the like. This means that Langdock’s search will not be better than that of SharePoint, for example.

If you want to understand how the approaches differ, you can read this blog post.

Similarities & Differences
Similarities
  • Both offer AI models from various AI providers, which are hosted in Europe in compliance with GDPR. Both offer a bring-your-own model.
  • Both offer a platform that can be used to automate processes.
  • Both platforms can be used to set up AI assistants and agents.
  • Both platforms are ISO27001 certified, but while amber is comprehensively ISO27001 certified, Langdock only has its processes certified, not its business premises.
  • Both solutions are GDPR compliant and comply with the EU AI Act.
amber
  • amber has dedicated support staff who provide long-term, regular support
  • amber is operated on the T Cloud – a sovereign cloud from a European provider
  • amber uses a technical approach, that does not have the limitations of MCP
  • amber offers significantly more comprehensive integrations with both on-premise and cloud solutions
  • amber has exclusively European shareholders
  • amber offers more flexible pricing packages that are better suited to the needs of larger companies
  • amber works according to SOC2 standards
Langdock
  • The German Langdock entity is 100% owned by an american entity, hence Langdock is directly dependend on US legislation
  • Langdock hosts with American hyperscalers.
  • Langdock is owned by an American holding company
  • Langdock is SOC2 certified