Lokalaise connects files, SharePoint, DMS, and and email into one knowledge layer that backs every answer with your documents and automates recurring work — run locally, GDPR-compliant, and and fully managed by us.

100% locally operatedGDPR-compliantproductive in 14 days

Key facts

Trusted by teams whose data must not leave the building.

100%locally operatedall data stays inside your company
14 daysto the first use casefrom kickoff to productive use
GDPRcompliantdata protection with no extra effort for you
1 : 1every answer with a sourceevery statement leads to the original document

01The situation

Right where cloud AI fails, your most important data lives.

Your most valuable knowledge sits in files, contracts, emails, and and scans — scattered, sensitive, and and off-limits for public cloud AI.

1.1

Knowledge is scattered

PDFs, file servers, SharePoint, emails, and and scans — your knowledge is fragmented across teams and systems.

1.2

Cloud is not an option

Project, customer, and and contract data is too sensitive to entrust to public cloud AI.

1.3

No AI team in-house

Building, operating, and and rolling out AI takes data engineers and AI specialists — and the market barely offers them.

1.4

Tools without tangible impact

Copilot and the like are running — yet efficiency and workflows don't improve measurably.

The result: hours are lost to searching, processes stay manual — and risks remain hidden in the data.

02Lokalaise Knowledge Layer

One knowledge layer from all your sources.

The Knowledge Layer connects your systems into a searchable, permission-aware knowledge layer — inside your company network.

Internal company network

Sources — existing systems · no migration

  • File server
  • SharePoint
  • DMS
  • Email
  • Scans

Knowledge Layer

indexedpermission-awareversioned

One index across everything — every match knows its source, permissions and version.

Answers with sources

Every statement backed by a source reference.

Automated workflows

Recurring processes run on their own.

You don't run an AI project. You get a finished, measurable result — as a managed local stack.

03Lokalaise platform

One platform for knowledge and work.

Four capabilities, one system. Pick one — on the right you'll see what it looks like in everyday work.

Lokalaise Chat · Project team

localpermission-aware

M. Petersen · 09:14

Which change orders are still open for Elbkai 12?

Lokalaise · 09:14

Three change orders are open: N-07 (foundation), N-11 (MEP) and N-14 (facade). N-11 has been awaiting the client's approval since May 21.

Change_orders_EK12.xlsxSharePoint · as of today, 07:40

Live example — ask conversationally, get an answer with evidence

04Agents

Digital coworkers — with owners, rules, and a duty to prove themselves.

Lokalaise agents take on defined tasks, ask when they get stuck — and improve night after night.

4.1

Clear ownership

Every agent has an Agent Owner — a person who is accountable, often IT or Lokalaise — and one or more Agent Feedback Givers the agent contacts when it has questions.

4.2

Starts in shadow mode

Agents are set up for defined tasks and initially run in parallel with the existing process — they have to prove themselves before they take over.

4.3

Asks instead of guessing

Agents notice when they can't do something and actively request feedback — for example via a Teams message to the people in charge.

4.4

Improves every night

Failed runs feed into a new version overnight, which is tested against the current one. If it improves, the Agent Owner is pinged automatically and decides on deployment based on evidence.

4.5

Strict boundaries

What an agent is not allowed to do is firmly defined — for example, approving invoices only up to defined amounts. Anything beyond that goes to a human.

4.6

Time for value creation

Agents bring transparency, traceability, and efficiency to recurring processes — and free up time for real value creation.

05Data sovereignty

Your data stays with you.
Completely.

The entire AI runs on your infrastructure. Every answer is traceable — down to the source.

Comparison: Lokalaise, cloud AI, and and building in-house by data location, permissions, traceability, auditability, time to productive, model choice, and and operations
CriterionLokalaiseCloud AIBuild in-house
Data locationYour data center. No document ever leaves the building.the vendor's serversown infrastructure, self-operated
PermissionsPermission-aware down to the answerdetached from your permission modelbuild it yourself
TraceabilitySource, version, and and history for every answerblack boxdepends on your build
AuditabilityEvery answer and every agent run in the audit traillittle insight into processingbuild it yourself
Time to productiveFirst productive answers from day 1, first use case live after 14 days1 day — but with no connection to your company knowledge3+ months to first value
Model choiceModels swappable, knowledge layer staystied to the vendorevery migration is a project
OperationsManaged by Lokalaiserequires your own AI team

§ 1

On your hardware

All processing — indexing, models, answers — runs in your data center. There is no outbound connection to external AI providers.

§ 2

Permissioned & auditable

Whoever asks a question only sees what they are allowed to see in the source systems. And if anyone wants to know: the audit trail shows who asked what, when — and which sources were used.

§ 3

No vendor lock-in

When a better model appears, we swap it in — your knowledge layer, agents, and and permissions stay unchanged. You commit to your data, not to a vendor.

06Gets better every night

An AI that adapts to your company.

The Lokalaise Knowledge Layer and Agent Layer keep adapting to your company, every night.

Every night

your AI keeps adapting to your company — entirely on its own.

6.1

Learns every night

Usage signals, feedback, and source quality automatically improve results, ranking, and answer precision.

6.2

Agents compound

Every implemented agent makes the system noticeably better and faster — and the next agent builds on everything the previous ones have learned.

6.3

Your knowledge grows with it

New documents, projects, and sources continuously expand the knowledge layer.

07Industries

For industries whose data must not leave the company.

Confidential documents, established processes, no in-house AI team — many industries know this pattern. That is exactly what Lokalaise is built for.

Construction & planning

Plans, expert reports, site diaries, contracts

Engineering & plant construction

Specifications, standards, test protocols

Industry & manufacturing

Work instructions, QA documentation, maintenance

Legal & consulting

Contracts, briefs, correspondence

Finance & insurance

Contracts, policies, audit reports

Research & public sector

Applications, official notices, tender documents

A fit if

  • Your expertise lives in documents, plans, and emails
  • Your data is too sensitive for the cloud
  • You don't have an in-house AI team
  • Approvals, reviews, and knowledge searches are done by hand

Your industry isn't listed? What matters is the pattern — not the industry.

08Rollout

Productive in 14 days, not months.

We start with an explicit use case, prove the value in real numbers, and grow from there.

Day 1–2

Goal & metrics

We define the first use case, the data sources, and the metrics the value must be measured against from day 14.

Day 2–12

Integration & workflow

Connect sources, index, inherit permissions — and the first use case takes shape on your real data.

Day 12–14

Go-live

The use case goes live in day-to-day operations. From day 14, the value is measured against the agreed metrics.

Day 1Day 7Day 14
Goal & metrics
Integration & indexing
Use case & permissions
Go-live on real data

measurement starts on day 14 — if the value shows in real numbers, we scale across teams, sources, and departments

09Model

As predictable as a subscription, with no surprises.

A clear, recurring model: one-time onboarding, the platform including hardware, and optionally managed agents. We share concrete pricing openly in a first conversation.

Setup & onboarding

one-time· per node

Setup, connectors, indexing, and permissions — all the way to go-live.

Core

Platform incl. hardware

monthly· per node

Inference, models, agents, and the knowledge layer — with evidence and audit.

Managed agents

monthly· per agent

Effective agents, continuously managed: monitoring, tuning, and benchmarks.

We size the hardware to match your users, agents, and workload — you only pay for what you actually need.

10Questions

What decision-makers want to know first.

The most common questions before a first conversation — answered in detail.

No. All processing — indexing, models, answers, and agent runs — happens on hardware in your data center or your internal company network. There is no outbound connection to external AI providers, neither for requests nor for training or telemetry. Data sovereignty stays entirely with you, and the GDPR assessment becomes significantly simpler because no data is transferred to third parties.

Every statement in an answer is backed by the source it comes from — including document, version, and exact location. You can check any claim against the original with a single click. Anything that cannot be substantiated from your documents is not claimed; the system will say it found no reliable source instead of guessing.

No. Lokalaise is a managed service: we handle setup, operations, maintenance, model updates, and the ongoing tuning of the platform. Your IT stays involved where access, permissions, and infrastructure are concerned — but does not have to hire AI specialists or operate models. We also set up agents together with your subject-matter experts.

First productive answers on your company knowledge are possible from day 1 after the sources are connected. The first defined use case goes live after 14 days. Measurement starts on day 14: before the start, we agree on metrics the value must show up in — and only once the numbers prove the value do we scale across additional teams, sources, and departments.

Yes, completely. Lokalaise inherits the user roles and permissions from your source systems — such as SharePoint, file servers, or DMS. Each person only sees content in answers that they would also have access to in the source system. In addition, the audit trail transparently logs who asked what and when, and which sources were used.

Connected systems include SharePoint, file servers (SMB), email (Exchange), Confluence, as well as ERP and DMS systems; PDFs and scans are also made searchable via text recognition. There is no data migration: your source systems remain the system of record, Lokalaise indexes them and keeps the index up to date. If a connector is removed, your data stays unchanged exactly where it has always been.

Then you benefit from them without rebuilding anything. The models are an interchangeable component of the platform: we evaluate new models, test them against the current setup, and swap them in when they are demonstrably better. Your knowledge layer, your agents, and your permissions remain unchanged throughout — there is no lock-in to a specific model or provider.

Through clear ownership and strict rules. Every agent has an Agent Owner who decides on deployments, and Feedback Givers the agent contacts when it has questions. New agents initially run in shadow mode in parallel with the existing process and have to prove themselves there. What an agent is not allowed to do is firmly defined — for example, approvals only up to defined amounts — and every run is traceable in the audit trail.

Local AI infrastructure

Your AI runs on your premises — not on someone else's servers.

Connected knowledge, grounded answers, and automated workflows — on your own infrastructure.

100% locally operated · GDPR-compliant · productive in 14 days

Contact sales