ABOLTUSA Brighter Tomorrow, Together.
PEOPLE. IDEAS. TECHNOLOGY.
ABOLTUS is building an AI workspace that turns your documents
into connected knowledge, projects and CRM.
A new chapter in human-centered AI. In development.
TWO DIRECTIONS. ONE STARTING POINT.
ABOLTUS is developing two ways to put the documentation you already have to work: build a project around it, or organize it into connected customer knowledge.
Turn specifications, contracts, meeting notes and research into a proposed project: goals, requirements, tasks and acceptance criteria, each connected to its source.
Bring customer knowledge out of contracts, quotations, invoices and correspondence. Prepare connected company, contact and agreement records with evidence you can inspect.
Both directions are in development. Proposed records and project structures are designed for human review.
MEET YOUR NEXT WORKSPACE
Our platform in development brings document search, source-aware AI answers and workflow automation together, with you in control.
Find the connection between a document, an idea and your next decision. Explore knowledge with the original source always in view.
Illustrative sample data · Explore the concept
FROM INFORMATION TO POSSIBILITY
Useful technology should make the next step clearer. Our work connects three parts of that journey.
Documents, records and notes become the starting point for a more connected way of working.
DOCUMENTS + DISCOVERYSource-aware search and contextual AI help turn scattered information into a clearer view.
CONTEXT + INTELLIGENCEConnect insight to a task, a conversation or a workflow, with people deciding what happens next.
PEOPLE + ACTIONDIFFERENT AMBITIONS. SHARED POSSIBILITIES.
From personal discovery to team collaboration, we’re exploring where connected intelligence can make a meaningful difference.
Find the thread in your notes, rediscover useful knowledge and give your next idea somewhere to grow.
Explore for yourselfBring documents and decisions into context, so knowledge can travel with the people who need it.
Explore for your teamExplore connections between business records, customer knowledge and the work that moves your organization forward.
Explore for your businessTHE IDEA BEHIND ABOLTUS
We believe technology should expand human potential. Help people understand more. Create more. And move forward on their own terms.
ABOLTUS connects artificial intelligence, business, openness, liberty, trust, unity and systems. A name with a purpose: more possibilities for you.
Read the project overviewTHE PROJECT IN DEPTH
A connected workspace for understanding your information, noticing meaningful changes and deciding what to do next. This is the direction of our research and development.
ABOLTUS starts with a practical question: how can the information you already have become easier to understand and use? A project can leave its knowledge scattered across documents, spreadsheets, messages, websites and business records. Finding a file is only the beginning. You also need to know which version matters, how it relates to other work and what changed since your last decision.
Our idea is to bring document discovery, connected knowledge and workflow automation into one understandable workspace. For an individual, that could mean following an idea through years of notes. For a team, it could mean tracing a decision back to the records that support it. The aim is to help people move from information to a considered next step.
Two distinct directions make this idea practical. Creating projects from existing documentation means turning specifications, contracts and notes into a proposed structure of requirements, tasks and acceptance criteria. Each item should preserve its source, with responsibilities, missing information and proposed changes available for review.
Building a CRM from your organization's documents means organizing customer knowledge already held in quotations, agreements, invoices and correspondence. Proposed company, contact and agreement records would connect that information to projects and relationship history. Both directions are in development and are designed around evidence, clear access boundaries and human approval.
The development plan begins with reliable access to original documents and their context. Search results should help you open the relevant passage, identify its source and understand the relationship between related records. A knowledge graph can provide another route through those connections, while ordinary text search remains useful for exact terms and familiar phrases.
AI assistance is planned as an optional layer. When a suitable model is available and its use is permitted, it could help explain retrieved material or prepare a draft answer with supporting references. The plan also includes search based on word forms and linguistic relationships without requiring a generative model. Keeping these modes explicit should make it clear whether you are reading a source excerpt, exploring a connection or reviewing generated text.
The project research explores a living data feed: a place where changes become understandable stories with evidence and possible next steps. With permission to use the selected sources, the planned system could connect an updated spreadsheet, a new attachment and a related business record. Each item would explain what changed, where the information came from and why it might deserve attention.
For example, a purchasing team could review a difference between an approved price and an invoice. A project coordinator could investigate conflicting delivery dates. These are intended use cases, with the original records available for checking. Relevance, uncertainty and user feedback matter here: a useful feed should help people focus rather than turn every small change into another interruption.
Understanding a problem should lead naturally to an appropriate action. Our workflow direction connects an observation to a task, a proposed reply, a comparison or a repeatable process. An assistant could help prepare the work, while the person responsible reviews the evidence and approves consequential actions.
The implementation plan treats permissions, execution history, cancellation and recovery as part of the workflow itself. A repeated request should not accidentally repeat an external action. A failed task should leave an understandable status and a way to recover. Early scenarios will need to demonstrate these behaviours before broader automation is offered. The purpose is to make routine work easier to supervise and improve.
The current desktop plan prioritizes a Windows application with separate data, settings and access boundaries for each Windows user. Core document access and search are intended to remain useful without an AI service. Local models and external providers are separate options to evaluate, with explicit choices about what information they may receive.
Collaboration introduces another question: what should be shared, with whom and on which devices? The synchronization plan proposes selected collections, visible version history and explicit device pairing. Conflicting edits should remain available for review instead of being silently overwritten. Offline access, permission changes and reconnection all need testing. These design requirements guide development; they do not imply that every collaboration feature is available today.
The implementation roadmap starts by identifying the actual documents, languages, users and workflows a pilot must support. A working desktop foundation comes next, followed by controlled document ingestion, search and the linguistic graph. Optional AI assistance, approved workflows and selected integrations build on that foundation. Data migration, backup, recovery and installation are also part of the plan.
Each stage needs clear acceptance criteria. Can a user find the right passage? Are restricted documents excluded? Does processing resume after an interruption? Are source links still meaningful after an update? Tests with representative collections should answer these questions before larger pilots. Capacity and speed must be measured on the relevant files and hardware, so we do not present planning targets as proven performance or promise a release date before validation.
This direction draws on the project's source-code research, its current AndForU implementation plan, and the living data feed concept. The accompanying research library covers information retrieval, relationships between documents, process discovery, distributed systems and human oversight. These areas help us identify useful methods and the limitations that need investigation.
A published method or a promising prototype is a starting point for evaluation. Its usefulness depends on the user's documents, language, permissions and working context. Our planned approach is to compare search results, inspect supporting evidence, test failure cases and collect feedback from real workflows. That feedback should shape which capabilities are developed further and how they are explained to the people using them.
ABOLTUS is intended for people managing personal knowledge, teams sharing project context and organizations exploring business automation. The most useful early conversations start with a concrete situation: a document that is hard to find, a change that is easy to miss or a task that repeatedly needs manual coordination.
You can explore the concept on this page and register your interest in early access. Tell us which sources you work with, what decision you need to make and where the current process becomes difficult. The wider platform remains in development. Your input can help turn the research and implementation plan into a workspace that fits practical needs.
A LITTLE MORE CLARITY
Here’s where we are, and where we’re going.
ABOLTUS is a developing technology project focused on AI, connected knowledge and automation. Its direction brings together work on document discovery, source-aware answers, business workflows and collaboration.
This is a dedicated development direction: use specifications, contracts, notes and research to prepare a proposed project with requirements, tasks and acceptance criteria. People review the scope and confirm the relevant version. Explore projects from documents.
The planned workflow would organize customer knowledge from contracts, quotations, invoices and correspondence into proposed company, contact and agreement records, with source evidence and reviewed relationships. Explore CRM from documents.
The website is live; the wider platform is in development. You can explore an interactive concept above and register your interest in early access. The preview uses sample data and does not connect to your files or run a live AI model.
The project includes local document search and change tracking, connected document knowledge, and a Windows-based multi-computer AI prototype. Business automation and proactive assistance are further areas of research and development.
Local processing, visible sources and explicit access controls are central to our direction. The website preview runs on sample data in your browser. The early-access form only collects the details you choose to submit. Read the website privacy notice.
Individuals, teams and organizations interested in shaping a more connected workspace. Tell us what you would like to explore. Registering interest does not create an account or guarantee an access date, and there is no payment at this stage.
THE NEXT CHAPTER STARTS WITH PEOPLE
Have a challenge, an idea or a different way of seeing things? We’d like to understand what would be useful to you.