The Enterprise Intelligence Network

Your data speaks. Every day.

Unfortunately, often at the same time and rarely in the same context.

InfoScape integrates seamlessly into your existing system landscape. It connects systems and knowledge sources, puts data into context and turns it into clear decisions and concrete measures. Building block by building block to create an enterprise intelligence network.

Data in. Context on top. Action out.

As individual as your vision. Think big. Build your version.

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InfoScape | Made in Germany
InfoScape | GDPR compliant
InfoScape | AI Model
InfoScape | In every cloud
InfoScape | On Premises
InfoScape | AI Act Conform
InfoScape | AI Model
InfoScape | Made in Germany
InfoScape | In every cloud
InfoScape | GDPR compliant
InfoScape | On Premises
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Innovation through collaboration

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InfoScape | Partner logo
InfoScape | Partner logo
InfoScape | Partner logo

Your data speaks.
Only the context is missing.

Data is created everywhere – in tools, tickets, documents and systems. But without context, hours can be lost on searching instead of acting. InfoScape connects everything into an enterprise intelligence network so that information can be turned into decisions.

More than data integration: Enterprise Intelligence.

More than data integration: Enterprise Intelligence.

Your data speaks.
Only the context is missing.

Data is created everywhere – in tools, tickets, documents and systems. But without context, hours can be lost on searching instead of acting. InfoScape connects everything into an enterprise intelligence network so that information can be turned into decisions.

Secure enterprise AI without data spills.

Enterprise AI,
that passes audits.

Security and governance are considered from the outset: central policies, logging and least-privilege access instead of uncontrolled AI growth. No black box: every response is traceable – with an audit trail and source path. Seamless integration into your existing system landscape (on-prem, cloud or hybrid).

Secure enterprise AI without data spills.

Enterprise AI,
that passes audits.

Security and governance are considered from the outset: central policies, logging and least-privilege access instead of uncontrolled AI growth. No black box: every response is traceable – with an audit trail and source path. Seamless integration into your existing system landscape (on-prem, cloud or hybrid).

Problem

AI has to have economical benefits for enterprises

GenAI is only half the battle

From design to decision. From decision to action in the system. GenAI brings speed, operational AI combines rules and data with action.

Data debt grows faster than projects

Data grows, context frays, quality drifts. Without disciplined pipelines and intelligent reuse of existing data, every use case starts from scratch and the ROI stalls.

Governance becomes the bottleneck

Black box AI does not pass an audit. Transparency, source origin and controls are mandatory, otherwise approvals are delayed and the implementation stalls.

Standard AI has its limits

Your current AI solutions struggle with complex contexts, growing data volumes and the efficient use of resources and often work more slowly in practice than promised.

Data sovereignty is slipping

Many AI services want sensitive data to leave external clouds… A risk for confidentiality, compliance and your sense of security.

AI without context remains superficial

Your data is stored in silos, in countless formats and systems. The models only see excerpts, so that connections and meaning remain invisible.

One-size-fits-all AI?

Relying on a single AI system or provider can lead to performance limits, dependencies and expensive dead ends.

AI could become an “algorithmic insider”

Little AI assistants are popping up everywhere, often with more rights than any person: they access mail, docs & systems, can be jailbroken and bypass the security team.

Solution

InfoScape – Answer in, action out

AI is becoming a business enabler

InfoScape turns answers into results. Smart Search, Meeting Intelligence and the AI Assistant bring knowledge into the workflow & lead to decisions and actions in the core system. Traceable, controllable, productive.

From data chaos to knowledge network

InfoScape connects systems to form an enterprise intelligence network. Content is structured, contextualized and reusable. Source path & versioning ensure quality and speed for new use cases.

Secure, transparent and compliant AI

On-prem or cloud-agnostic, you retain full control over your data: no black box (every response is traceable), model-agnostic, and geared towards GDPR and EU AI Act compliance.

AI that grows with you

You get an adaptable AI system with a strong understanding of context that processes large amounts of data, makes performance measurable and consumes as little energy as possible.

Your data where it belongs: with you

You retain full control: integrated into your architecture according to your specifications, clear data paths, no hidden outflows. Winners keep their data in-house.

Context + data = success

Your data is linked and structured in such a way that AI can actually categorize it: not just find it, but understand it and put it into context – with a proprietary way of combining data into a conceptual landscape.

Relying on many specialists

With InfoScape, you get diversity instead of monoculture: different, combinable AI modules for different tasks that are interchangeable, expandable and future-proof.

Thinking about compliance from the outset

You work with a solution that takes legal requirements seriously: Traceability, documentation and clear guidelines ensure that you are on the safe side from a regulatory perspective.

On-Premises

A centrally controlled platform with uniform policies, logging and least-privilege access, which can be expanded to include customized agents and can also be operated completely on-prem.

InfoScape is the AI tool that works where your data lives.

It understands your data across systems, combines information logically and creates transparency. This turns fragmented information into a precise, reliable decision-making machine.

Made in Germany. And that’s where your data stays – no matter how global your enterprise is.

What makes InfoScape so unique?

Language-centered thinking

On-device voice recognition enables natural interaction with InfoScape via voice while sensitive data remains within the company.

Turning structured and unstructured data into usable knowledge

InfoScape combines search/database queries with AI search prompts and gives the models long-term memory + in-house knowledge. This results in verifiable answers instead of black boxes.

Context instead of individual knowledge

InfoScape recognizes which information belongs together, automatically closes knowledge gaps and continuously learns from user queries. As a result, answers in everyday life become increasingly accurate over time.

Beyond GenAI

InfoScape is not limited to a single AI technology. The solution can use and combine different AI processes, today and in the future. In this way, companies avoid dependencies as well as performance limits and can continuously grow their AI landscape based on needs or challenges.

Sustainability

The way InfoScape prepares and structures data means that AI requires less computing power to provide good answers: this saves energy and reduces the carbon footprint of AI applications.

No black box

AI is only ready for business when results are verifiable. That’s why InfoScape provides answers with a source path and audit trail. This reduces risk, speeds up approvals and makes AI usable in critical processes.

The context advantage

AI rarely fails because of too little data, but because of a lack of context. InfoScape uses a proprietary method that structures enterprise data in such a way that correlations become clear for AI; across texts, key figures and metadata. The result: reliable answers, less guesswork, more reliable decisions.

Functions of InfoScape

Smart Search

Your employees ask a question – Smart Search searches your entire knowledge space semantically, not just by keyword. Documents are transformed into

processable data, linked and made searchable as a knowledge hub; including knowledge graph and context clues as to where information comes from.

Meeting Intelligence

Every meeting automatically becomes a knowledge object: real-time transcription (microphone & speaker), AI-supported notes, summaries in three levels of detail and exportable. Meetings can be tracked from preparation to conclusion with decisions, tasks and risks that become part of the intelligence network instead of disappearing in file folders.

AI assistant

Your personal assistant knows your data: Ask questions in everyday language, attach documents, speak by voice or work together in the platform. The assistant understands context, incorporates your documents via retrieval augmented generation and creates content ranging from summaries and drafts to structured templates, in multiple languages and in the right tone.

Integrations & Upgrades

InfoScape can dock onto your existing landscape via optional modules for specialized data sources: CRMs, specialist systems, IoT signals, analytics models or compliance tools can be connected and integrated into the knowledge space without you having to reinvent your infrastructure.

Agentic AI (Customization)

Customized, agent-based AI workflows can be set up for critical processes that take over end-to-end tasks; always based on your rules, data and security requirements.

Data Retrieval

Structured and unstructured data become a common context model in InfoScape. This means that the platform can not only search content, but also understand and categorize it – across sources.

Use cases

Construction industry

AI-protected Data Explorer for error message analysis

Problem

The central challenge was to evaluate around 900,000 monthly error messages from various sources in such a way that causes could be quickly identified and the teams could switch from reactive rework to preventive control.

Our solution

Central, AI-supported Data Explorer
All error messages are transferred from the previous silos to a standardized, searchable view.

Pattern and cause analysis
InfoScape groups similar messages, recognizes recurring error patterns and shows probable causes and affected systems.

Self-service instead of putting out fires
Departments can filter, drill and track trends independently – with a focus on prevention instead of manual correction.

Aviation industry

Comprehensive employee survey – Management Board report

Problem

The main challenge was to combine statistical results and open comments in such a way that a comprehensible Board of Management report was created: with a clear mood, comprehensible priorities and concrete areas of action instead of a confusing collection of data.

Our solution

Numbers and voices in one screen
Numbers, free text and metadata are connected in a shared knowledge space – instead of being stored in separate dashboards and lists.

Questions instead of searches
For every management question, InfoScape automatically pulls together the appropriate key figures and original comments and shows not only what, but why.

Reliable, trustworthy data basis
The result is a compact board report with clear priorities that can be traced back to the individual figure or statement – far beyond classic BI reports and standard AI chatbots.

Mechanical engineering and supplier industry

Prediction of completion dates from MES data

Problem

Completion dates and machine running times could only be roughly estimated from the MES data – there was a lack of AI-supported forecasts that would enable reliable planning despite incomplete data quality.

Our solution

Making MES data visible
MES and additional data is cleansed, standardized and prepared as a basis for AI-supported predictions.

Learning process model
An AI-supported algorithm learns a parameterized process graph from historical orders that depicts real processes, bottlenecks and restrictions.

Forecasts where decisions are made
Scheduling and planning have access to completion and runtime forecasts as well as what-if scenarios via a lean plug-in – without the need for in-house modeling expertise.

Legal sector

AI search for “Law in the workplace”

Problem

Users of a compliance platform have to work with complex search masks and many categories to find the right guidelines and evidence. This takes time, requires specialized knowledge and tends to put off occasional users.

Our solution

Simple interface with search field
Instead of masks and dropdowns, there is a search slot – a question in everyday language is enough.

AI-supported categorization
The AI analyzes the request, derives suitable categories from the compliance database and asks questions for clarification if necessary.

Automatic intersection search
The existing intersection search is carried out in the background with the recognized categories; the hits are displayed in a clear results list.

Insurance industry

Data processing for forecasting, error prevention & operational control

Problem

The central challenge was to prepare highly fragmented operational, campaign, support and system data in such a way that it could be used as a reliable basis for forecasting, error prevention and operational control – instead of as a heterogeneous data mix.

Our solution

A data foundation instead of data silos
Different sources (e.g. support, systems, master data) are transferred to a uniform schema and a common timeline, including pseudonymization of sensitive fields.

Clean, traceable data streams
Formats are standardized, timestamps normalized, gaps and outliers marked, duplicates removed > All steps are logged.

Forecast-ready & AI-capable
Consistent events are created from log and process data; the result is a versioned data foundation for reliable forecasts, reports and LLM queries.

Retail sector

AI inventory tool

Problem

Inventories are time-consuming, labor-intensive and require store closures while products have to be counted manually and compared with the inventory list.

Our solution

Visual stocktaking via iPad
Shelves are scanned by camera instead of counting items individually.

AI-supported matching
The AI recognizes books and products on the shelf and automatically matches them with the inventory list.

Designed for store operations
The solution reliably processes shelf and room recordings to create an up-to-date stock overview.

Financial services industry

AI agent ensemble

Problem

It is extremely difficult for asset managers to consistently beat the S&P 500 with a concentrated 10-stock portfolio and only one rebalancing per week, while at the same time complying with risk targets, transaction costs and scarce quant resources.

Our solution

Systematic AI investment process
A population of trading agents generates specific buy and sell signals for the S&P 500 based on reinforcement learning.

Ensemble for robust alpha generation
The best agents are continuously selected, weaker strategies are automatically sorted out – this reduces model risk and regime breaks.

Built-in risk management
Trading frequency, position sizes and a turbulence index limit drawdowns and ensure a controlled risk/reward profile.

Construction industry

AI-protected Data Explorer for error message analysis

Problem

The central challenge was to evaluate around 900,000 monthly error messages from various sources in such a way that causes could be quickly identified and the teams could switch from reactive rework to preventive control.

Our solution

Central, AI-supported Data Explorer
All error messages are transferred from the previous silos to a standardized, searchable view.

Pattern and cause analysis
InfoScape groups similar messages, recognizes recurring error patterns and shows probable causes and affected systems.

Self-service instead of putting out fires
Departments can filter, drill and track trends independently – with a focus on prevention instead of manual correction.

From the: Aviation industry

Comprehensive employee survey – Management Board report

Problem

The main challenge was to combine statistical results and open comments in such a way that a comprehensible Board of Management report was created: with a clear mood, comprehensible priorities and concrete areas of action instead of a confusing collection of data.

Our solution

Numbers and voices in one screen
Numbers, free text and metadata are connected in a shared knowledge space – instead of being stored in separate dashboards and lists.

Questions instead of searches
For every management question, InfoScape automatically pulls together the appropriate key figures and original comments and shows not only what, but why.

Reliable, trustworthy data basis
The result is a compact board report with clear priorities that can be traced back to the individual figure or statement – far beyond classic BI reports and standard AI chatbots.

Mechanical engineering and supplier industry

Prediction of completion dates from MES data

Problem:

Completion dates and machine running times could only be roughly estimated from the MES data – there was a lack of AI-supported forecasts that would enable reliable planning despite incomplete data quality.

Our solution:

Making MES data visible
MES and additional data is cleansed, standardized and prepared as a basis for AI-supported predictions.

Learning process model
An AI-supported algorithm learns a parameterized process graph from historical orders that depicts real processes, bottlenecks and restrictions.

Forecasts where decisions are made
Scheduling and planning have access to completion and runtime forecasts as well as what-if scenarios via a lean plug-in – without the need for in-house modeling expertise.

Legal sector

AI search for “Law in the workplace”

Problem:

Users of the compliance platform have to work with complex search masks and many categories to find the right guidelines and evidence. This takes time, requires specialist knowledge and tends to put off occasional users.

Our solution:

Simple interface with search field
Instead of masks and dropdowns, there is a search slot – a question in everyday language is enough.

AI-supported categorization
The AI analyzes the request, derives suitable categories from the compliance database and asks questions for clarification if necessary.

Automatic intersection search
The existing intersection search is carried out in the background with the recognized categories; the hits are displayed in a clear results list.

Insurance industry

Data processing for forecasting, error prevention & operational control

Problem:

The central challenge was to prepare highly fragmented operational, campaign, support and system data in such a way that it could be used as a reliable basis for forecasting, error prevention and operational control – instead of as a heterogeneous data mix.

Our solution:

A data foundation instead of data silos
Different sources (e.g. support, systems, master data) are transferred to a uniform schema and a common timeline, including pseudonymization of sensitive fields.

Clean, traceable data streams
Formats are standardized, timestamps normalized, gaps and outliers marked, duplicates removed > All steps are logged.

Forecast-ready & AI-capable
Consistent events are created from log and process data; the result is a versioned data foundation for reliable forecasts, reports and LLM queries.

Retail sector

AI inventory tool

Problem:

Inventories are time-consuming, labor-intensive and require store closures while products have to be counted manually and compared with the inventory list.

Our solution:

Visual stocktaking via iPad
Shelves are scanned by camera instead of counting items individually.

AI-supported matching
The AI recognizes books and products on the shelf and automatically matches them with the inventory list.

Designed for store operations
The solution reliably processes shelf and room recordings to create an up-to-date stock overview.

Financial services industry

AI agent ensemble

Problem:

It is extremely difficult for asset managers to consistently beat the S&P 500 with a concentrated 10-stock portfolio and only one rebalancing per week, while at the same time complying with risk targets, transaction costs and scarce quant resources.

Our solution:

Systematic AI investment process
A population of trading agents generates specific buy and sell signals for the S&P 500 based on reinforcement learning.

Ensemble for robust alpha generation
The best agents are continuously selected, weaker strategies are automatically sorted out – this reduces model risk and regime breaks.

Built-in risk management
Trading frequency, position sizes and a turbulence index limit drawdowns and ensure a controlled risk/reward profile.

Is InfoScape right for you? Find out in the pilot.

Use case first

We start with a specific use case from your day-to-day business and define in advance how success is measured. Not a strategy pitch, but a test with real workflows.

And then it becomes scalable

A use case shows the way. Then InfoScape grows module by module: reporting today, operations tomorrow, engineering the day after tomorrow. Each step may be different – but everything ends up in the same Intelligence Network instead of in new individual solutions.

All advantages at a glance

GDPR

Your data remains under your control. No shadow copies, no hidden outflows.

Security

Each answer is backed up with sources and context. You don’t just see what the AI says, but why.

Speed

New searches do not start from scratch, but build on a growing network of knowledge.

Compliance

AI that is controllable and compatible with GDPR, EU AI Act & internal requirements.

Intuitive

Employees work with AI in their everyday language without training in tools, masks or query languages.

Sustainable

Our way of processing data enables leaner queries with less computing effort, less energy and more output per kilowatt hour.

Expandable

Where worthwhile, you can add specialized, agent-based workflows that take over end-to-end tasks.

Future-proof

You are not restricted to one model. InfoScape can orchestrate different AI building blocks, just as you need them.

Let’s AI together!

The path to successful integration of AI in your company starts with the right questions: where are your pain points, which use cases are really worthwhile, what do the database, security and governance look like? In our customized InfoScape AI workshops, we combine your practice with our experience and jointly develop an implementable AI strategy, concrete use cases and a clear roadmap for the introduction.

AI discovery & use case mapping

Together, we analyze your business areas, data sources and existing processes, identify the biggest pain points and translate them into concrete AI use cases. The result: a prioritized roadmap of where InfoScape has the greatest leverage in your company.

Benchmarking

Model-agnostic mini-benchmark (vendor-independent) that evaluates the quality of different AI approaches on your data and sets realistic expected values. Result: a well-founded recommendation for the choice of provider and architecture.

End-to-end agents

We translate a prioritized goal into an agentic task chain, outline a prototypical end-to-end agent and define a compact pilot plan. The result: a tangible picture of how InfoScape can work from input to action.

Cybersecurity screening

Short, honest security and compliance check for your AI use case (vendor-neutral) that examines feasibility and risks. Result: a clear go/no-go with concrete measures to close security gaps and accelerate approvals.

Discover AI workshops

InfoScape
Added value

InfoScape finally makes AI tangible: Instead of abstract promises, the software shows measurable results that directly improve your day-to-day work. Efficiency, cost control and process optimization become visible and plannable.

Up to

%

Reduction of bureaucratic costs

Up to

%

Cost savings in service operations*

Up to

%

Reduction of administrative costs

Up to

%

Reduction of expenses in supply chain and inventory management*

*Source: 2025 AI Index Report

Frequently asked questions and answers

Does InfoScape fit our requirements?

InfoScape is worthwhile if you have many distributed data sources, work with sensitive information and want more from AI than a chatbot. Typically, companies that need to make decisions traceable (e.g. board, HR, operations, compliance) and want to use AI under control – rather than in the shadows.

What advantages does InfoScape offer at a glance?

You get a central, AI-enabled knowledge base instead of many isolated solutions: higher data usage, faster prioritization, comprehensible decisions, less manual searching. Plus data sovereignty, integrated governance, energy efficiency and the option to set up specialized agents at a later date without vendor lock-in.

How does InfoScape integrate into our existing IT?

InfoScape connects to your existing landscape: File repositories, DMS, collaboration tools or specialist systems can be connected step by step as bookable integrations. We usually start with documents and meetings, then expand to include other sources (e.g. tickets, logs, IoT, analytics) and adapt the pace to your IT and security requirements.

How much does InfoScape cost?

The costs depend on three factors: Scope of integrations/customizations, number of users and chosen deployment model (SaaS, VPC, on-prem). We will clarify your requirements in a brief initial consultation and prepare a transparent offer after an initial workshop.

What support is available after implementation?

We don’t leave you alone after the go-live: we offer training for teams, technical support, monitoring and regular reviews in which we identify new use cases and optimize existing ones. On request, we can also take over the ongoing tuning of Guardrails, workflows and agents.

To what extent can InfoScape be individualized (customizations)?

InfoScape is an out-of-the-box solution with upgrade options. We can connect your own data sources (i.e. CRM), train domain knowledge, define company-specific guardrails and develop agent-based end-to-end workflows (e.g. reports, checks, ticket routing). We determine the scope and depth of the customization together with you.

How does InfoScape contribute to sustainability?

Thanks to our way of preparing and linking data, AI requires less computing power per response. You avoid redundant pipelines, reduce unnecessary requests to large models and can bring computing resources closer to your data – saving energy and infrastructure costs.

Who is behind InfoScape / TerraTech?

TerraTech Holding GmbH was founded in 2019. Our mission: to develop AI systems that are not only powerful, but also resource-efficient and secure, so that companies can benefit from AI without having to accept high barriers to entry or security risks. InfoScape has been our SaaS solution for corporate intelligence “made in Germany” since 2024.

Ready to take the next step with InfoScape?

Send us a brief description of your use case or your question and we will get back to you personally as soon as possible.

Whether you want to see a live demo, talk specifically about features & pricing or simply check whether InfoScape fits your situation: Simply fill out the form and together we’ll find the most sensible next step.