DssLayers

Digital transformation

The knowledge of all your systems in one private AI

10% 01 Analysis How you work today and where you lose time 20% 02 Criteria What AI can do and what it cannot 30% 03 Documentation Start with what is already written down 45% 04 Tools Every tool and what it is for 60% 05 Repetitive tasks What repeats itself happens on its own 75% 06 Your systems Without changing the software you already use 90% 07 Adoption Your team uses it from day one 100% 08 Evolution It is measured, improved, and it grows with you
02

Mission

A modular ecosystem that runs on your own server and works as one single system: conversation, documents, email, meetings, data and automation, built on the knowledge the company already has.

Mission

We turn what a company already knows —its documents, its files, its people's judgement— into an intelligence of its own that works inside its server and answers with the source in front of it.

Vision

That no company should lose what it knows: that the judgement of those who leave keeps answering, and that no question worth asking has to leave the building to be answered.

Everything happens inside your server nothing leaves the building 01 What you already know Documents Data Your team's judgement 02 Local Model 03 Answer with the source in front of you what is learned goes back to the knowledge base Everything happens inside your server nothing leaves the building 01 What you already know Documents Data Your team's judgement 02 Local Model 03 Answer with the source in front of you what is learned goes back to the knowledge base
Fig. 02 — From what the company already knows to an intelligence of its own · everything happens inside its server

Artificial intelligence as one more layer of the company's infrastructure —alongside the database or the intranet— and not as an external service you hand your information to.

03

Services

Our platform is a modular ecosystem of AI-assisted microservices that can work as one.

DssLayers CLUSTER 01 Hardware all in one package 02 Frontier models usage control 03 Local models total privacy 04 Microservices self-contained, 24/7 05 Database data and documents 06 AI intranet gateway DssLayers CLUSTER 01 Hardware all in one package 02 Frontier models usage control 03 Local models total privacy 04 Microservices self-contained, 24/7 05 Database data and documents 06 AI intranet gateway
01

Hardware

Server, graphics and memory delivered as one module: the platform arrives ready to run.

02

Frontier models

Frontier models by API, with usage control: per-user metrics and cost forecasting.

03

Local models

Processes that cannot leave the building run here: nothing leaves the server.

04

Microservices

Self-contained services, running 24/7, and not necessarily in the same place: document analysis, for instance.

05

Database

A centralised document database with all the company's information: ideal for training models.

06

AI intranet

An intranet built 100 % around artificial intelligence: the gateway to your company's digital transformation.

Technical drawing of layer 01: Hardware
Fig. 03 — Cluster architecture · six layers on DssLayers
04

DSS8 MicroModels

Everything the company says, writes and decides ends up in a knowledge base of its own: that is where the AI modules come from that know how things are done here.

What the company generates Conversations Documents Email Meetings Data The knowledge base it is built through use: every source adds a layer AI modules Finance how it is done here People the house's judgement Purchasing the usual suppliers Legal without leaving the building What the company generates Conversations Documents Email Meetings Data The knowledge base it is built through use: every source adds a layer AI modules Finance how it is done here People the house's judgement Purchasing the usual suppliers Legal without leaving the building
Fig. 04 — From what the company generates to its AI modules · the base is built through use

These are not finance models in general, but models of how finance is done here: they arrive once the base has enough material to teach them your judgement.

05

Industries

Five trades, one same platform: the same engine, applied to what each sector needs.

01 Firms professional secrecy 02 Industry the judgement that leaves 03 Engineering files that do not answer 04 Public sector what the inspector asks for 05 Services AI outside the building Sectors 01 Firms professional secrecy Cannot find what you know · The inspector · Information is pasted outside 02 Industry the judgement that leaves The one who knew retires · The margin shows up late · The inspector 03 Engineering files that do not answer Cannot find what you know · The one who knew retires 04 Public sector what the inspector asks for Cannot find what you know · The inspector 05 Services AI outside the building Cannot find what you know · The margin shows up late Information is pasted outside Shared problems The inspector may arrive tomorrow The one who knew retires the judgement was never written down Cannot find what you know the answer costs a phone call The margin shows up late the variance, at closing Information is pasted outside with no record and no control
Fig. 05 — Sectors and shared problems · click a box to read its file
01 · Professional firms

AI that respects professional secrecy.

Professionals in these firms already use generative AI. The question is not whether to use it, but how to do so without compromising confidentiality. Entering client data into public tools, even a fragment, can amount to a breach of professional secrecy. We deploy AI inside your secure environment so you can consult files, emails and contracts without the information leaving the firm.

Use case: «Have we told this client anything by email that contradicts what we agreed in the contract?» The AI answers inside the firm, with traceability and without exposing confidential data.

02 · Industry and construction

Technical judgement should not retire with people.

A significant part of the critical knowledge on the plant floor and on site sits with professionals who have years of experience. It is not in the files: it is in decisions, adjustments and exceptions that were never documented. When those people retire, the organisation loses its ability to respond. We deploy AI to capture and preserve that knowledge: internal assistants that answer with manuals, histories and technical criteria, without depending on whether the person who knows is there.

Use case: «Why is this machine adjusted this way on Mondays?» The AI answers with the history of adjustments and the documented criteria, even when the technician responsible is not available.

03 · Engineering and architecture

All your technical history, finally searchable.

In engineering and architecture, every proposal tends to start from scratch even when comparable projects exist. The judgement built up over years —solutions applied, change orders, cost overruns— sits scattered in files and folders that are not easy to consult. We deploy AI that structures and opens up that knowledge: your team asks in plain language and gets answers from the office's real history.

Use case: «What change orders did we have on jobs with a high water table, and what did they cost?» The AI answers with the projects, the line items and the amounts, without having to go through folder by folder.

04 · Public sector suppliers

Inspection paperwork, always ready to be proven.

As a public sector supplier, an inspection can require inventory, access control, traceability and training records at any moment. If that information is scattered or produced with public tools and personal accounts, it cannot be defended: there is no control and no traceability. We deploy AI in a private environment, integrated with your systems, so the data is structured and available for any request.

Use case: «What inventory, access and traceability can we prove today?» The AI answers with consolidated, dated and traceable records, ready to present.

05 · Services

Your team already uses AI. Now, with control and traceability.

In most organisations, the team already uses generative AI on its own initiative. Internal information goes into public tools, often from personal accounts and with no record. The result is a loss of control over the data and a total absence of traceability. We deploy AI in a private corporate environment: company accounts, usage logging, and data that does not leave the organisation.

Use case: «What information has left this week towards a public AI, and from which account?» With our deployment, the answer is available at any moment.

06

Contact

Tell us what your company does and what you would like to solve. We read every message and answer ourselves, with no middlemen.

Write to us

[email protected]

If it is a good fit, we will tell you where to start. And if it is not, we will tell you that too.

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