Skip to main content

AmaraCloud

A knowledge system for documents

AmaraCloud is a document-centred knowledge system with long-term memory for documents of every kind.

AI quick overview

  • What is the next step?

    A conversation about use case and data posture. Onboarding is guided. There is no public self-service.

  • What is A.M.A.R.A.?

    A.M.A.R.A. is Rieger Systems' intelligence layer – currently in development, not marketed as a standalone consumer product.

  • What does A.M.A.R.A. stand for?

    A.M.A.R.A. stands for: A Machine Always Ready to Assist.

  • Where do AI and data run?

    Operations and data flow are aligned to EU infrastructure. The core setup is designed without mandatory dependency on non-European cloud providers.

  • Do you sell our AI data?

    No. Data from AmaraCloud is not sold. Data sovereignty remains fully in Europe, and production compute also remains fully in Europe.

  • Does AmaraCloud run autonomous agents?

    No. People run the search, open the source and keep the decision. There are no free-running agents.

AmaraCloud

Every answer with the passage you can open.

Contracts, email, spreadsheets, images, policies: AmaraCloud keeps documents of every kind in long-term memory. Search does not stop at a sentence. It returns the evidence — snippet, place and the original passage.

  • Operated in the EU

    Data storage and production compute stay in Europe.

  • No data resale

    Data from AmaraCloud is not sold.

  • Guided onboarding

    A pilot with selected organisations. No public self-service.

Knowledge sits in files. Decisions need the passage.

An answer without a place is still a claim.

The same question returns across drives, mail and tickets: which version holds, and where is the sentence?

A filename search and an AI sentence are not enough. Before a decision, the passage in the original has to be open.

The same file, readable three ways

AmaraCloud turns each document into a structure you can check and a machine can read. Automation, analysis and the answer use it. Every value keeps its source.

Machine-readable

The original becomes blocks with a place: heading, paragraph, table, cell, mail part, image region, time span. A spreadsheet stays rows and cells, not a paragraph.

  • PDF
  • Word
  • Excel
  • PowerPoint
  • Email
  • Image
  • Audio
  • Text

Facts, grouped

Samples. The wording stays. Dates and amounts are also stored normalised. A missing value is not filled in.

Parties

  • Beispiel GmbH

    Issuer

    Rahmenvertrag-2024.pdf · Page 1

Amounts

  • €1,280 net

    Offer, 4 September 2026

    Angebot-Produkt-X.pdf · Page 2

Dates

  • 2026-10-15

    Due, wording 15 October 2026

    Rechnung-XYZ-091.pdf · Page 1

Identifiers

  • XX-AM 204

    Registration plate

    Fahrzeugzuweisung.pdf · Page 1

Quantities

  • 7 orders

    Last one in September 2026

    Auftragsliste-XYZ.xlsx · Sheet

  • Automation

    Workflows read fields, not prose: amount, date, identifier, quantity.

  • Analysis

    Cells, quantities and amounts stay comparable, with currency, unit and date.

  • Artificial intelligence

    The answer cites the passage. It does not set a value without a source.

The proof is the passage in the original

AmaraCloud does not stop at a sentence. Every hit names its place and opens there. Exact applies to a text layer or a known time span. A scan and an image region stay Region. A missing page is not invented.

Questions from a working day

Samples. Names, customers, vehicles and amounts are invented. Not a live request.

Choose a question. It runs only after you send.

No question selected

Send

Example · not customer data

Each question opens its own source.

  • A place, not a claim

    Page, cell, image region or time span. A hit without a place is not a hit.

  • Open the original

    Preview jumps to that place. You read the source, not only the summary.

  • Honest precision

    Exact for a text layer or a known time span. A scan and an image region stay Region. A missing page is not invented.

How a file becomes a structure

Ingest, a machine-readable structure, grouped facts, then the source. Relations between documents are the direction.

Upload

Documents of every kind are ingested, checked and stored with a content hash.

Machine-readable

PDF, Office, spreadsheets, email, images, audio and text become blocks with a place. A spreadsheet stays rows and cells.

Facts

People, organisations, identifiers, dates, amounts, quantities and places, grouped. The wording stays, the value is normalised.

The same structure

Search, automation, analysis and the answer read it. You open the source and decide.

Search becomes checking

Full text carries search. Semantic retrieval can join in without blocking it.

AmaraCloud ingests documents of every kind, writes them in a machine-readable form and attaches every value to a source location. Full text carries search. Semantic retrieval can join in without blocking it.

Relations between documents are the direction. The pilot promises the evidence you can open first — not a finished knowledge graph, and not one industry.

What AmaraCloud also carries

The source is the proof. The structure is what machines read.

Machine-readable

PDF, Office, spreadsheets, email, images, audio and text become blocks with a place.

Facts

Grouped as parties, amounts, dates, identifiers and quantities. The wording stays.

Content hash

Every upload is checked. The hash stays with the document, for files of every kind.

Visible index stage

Each document shows how far ingestion has got.

Same trail

Questions and search return the same evidence.

Tenants

Separate spaces and roles.

Relations

The direction between documents. The pilot delivers the source location first.

Not tied to one industry

Any organisation whose knowledge sits in documents.

Many places

Contracts, email, spreadsheets, images and policies.

Before the decision

Specialists who check an answer.

Repeated questions

Service, operations and backoffice.

Data location

Organisations with requirements on tenant separation.

First cut

Document-heavy teams. That cut is the entry point, not the product boundary.

Limits and responsibility

What AmaraCloud does not promise.

No guarantee of correctness

The evidence is there. The decision stays with people.

No autonomous professional decisions

Not in law, medicine or finance.

No polished precision

A scan is a region, not an exact text span.

No free-running agents

People open the source and decide.

Guided onboarding

A pilot with selected organisations, not public self-service.

The layer under AmaraCloud, not the product itself.

A.M.A.R.A. (A Machine Always Ready to Assist) is the in-house foundation. It is in development and not a finished consumer product.

Short answers

What AmaraCloud is, what counts as evidence, who it is for, and what happens next.

What is AmaraCloud?

A document-centred knowledge system: documents become machine-readable, facts are grouped, and every answer opens its source. For any industry and any use case.

What counts as evidence?

A snippet plus a place — page, cell, image region or time span. You open that place and check it yourself. A scan or a picture without a text layer stays a region. For audio the time span is exact, not the single word.

What does a file become?

Blocks with a place: text, table, cell, email, image region, time span. Grouped facts from that — people, organisations, identifiers, dates, amounts, quantities, places. Dates and amounts are also stored normalised. The same structure feeds automation, analysis and the answer.

Who is it for?

Organisations whose knowledge sits in documents, in any industry. The first pilot cut is document-heavy teams. That cut is the entry point, not the product boundary.

AmaraCloud is available now, on request

We look at the use case, the sources and what evidence has to mean in your day. Onboarding is guided, data stays in the EU, and nothing is sold.