The knowledge your people need already exists inside your organisation — buried in documents, locked inside experts' minds, decaying in unmaintained repositories, invisible behind the wrong search query. Astraal Horizon makes it findable, alive, and permanently yours.
The knowledge crisis in most organisations is not a volume problem. It is a visibility, currency, and connectivity problem. Knowledge exists everywhere — in documents nobody can find, in experts nobody can locate, in processes nobody has documented, in decisions nobody has recorded. The moment someone needs it, it might as well not exist. Astraal Horizon was built to end organisational knowledge invisibility.
Named for the way knowledge behaves — always expanding at the edge, always connected to everything it touches — the Knowledge Horizon Engine™ builds a living knowledge graph of your organisation that grows smarter every time someone searches, creates, or shares anything.
The Knowledge Horizon Engine™ constructs and continuously maintains a multi-dimensional knowledge graph of your organisation — mapping documents, expertise, tacit knowledge, decision records, and knowledge relationships across the entire enterprise. It infers expertise from behaviour, detects knowledge decay before it becomes invisible, surfaces contextually relevant knowledge at the moment of need, and connects the right people to the right knowledge nodes automatically.
Built around the four things knowledge must do to be genuinely useful — be found, be trusted, be preserved, and be governed — each pillar designed so that knowledge works harder the longer it exists inside Horizon.
The most important thing a knowledge platform must do is make knowledge findable — not just searchable. Discovery goes beyond returning results to understanding intent, surfacing connections, and delivering knowledge in context.
AI-powered search that understands intent, context, and knowledge relationships — returning relevant nodes, related experts, connected documents, and decision records rather than a list of keyword-matched files.
Graph-traversal recommendations that surface what the searcher did not know to look for — adjacent knowledge nodes, cross-domain connections, and historical precedents that frequently contain the most valuable insights.
Proactively delivers knowledge to people inside their workflows — surfacing relevant resources inside Astraal LXP pathways, SkillSphere skill gaps, and Xperience community discussions before they need to search.
The most valuable knowledge in any organisation is in the minds of its experts — and most organisations have no reliable map of who those experts are, what they know, or how to reach them.
Expertise maps built from evidence — content creation, question resolution, peer citations, project contributions — rather than self-declaration. Every person's expertise profile is continuously updated from what they actually do, not what they claim on a form.
When a knowledge seeker reaches the edge of what documents can answer, Horizon surfaces the right internal expert — with context about why they are matched, a relevance score, their availability, and a contextual introduction to start the conversation well.
A queryable, real-time map of who in the organisation knows what — browsable by domain, topic, depth of expertise, and availability. For L&D leaders, a resource for finding internal faculty. For talent teams, a succession intelligence tool.
Knowledge does not just go missing when people leave — it decays silently while they are still there. Knowledge Continuity prevents both forms of loss through proactive capture, structured transfer, and continuous currency monitoring.
A structured, AI-facilitated knowledge transfer process triggered when a key employee announces departure — capturing tacit knowledge, decision rationale, relationship context, and undocumented expertise before it leaves the building.
Tracks the currency health of every knowledge node — detecting when content becomes stale relative to external signals and alerting knowledge owners or triggering automatic validation requests before anyone unknowingly relies on outdated information.
Converts unstructured knowledge sources — recorded meetings, expert Q&A sessions, Slack conversations, email threads — into structured knowledge graph nodes through AI extraction and expert validation workflows.
The institutional control layer — giving knowledge managers, L&D heads, and CKOs the intelligence and governance tools to treat organisational knowledge as a managed strategic asset rather than an uncontrolled byproduct of work.
Real-time measurement of knowledge health across every domain, function, and knowledge type — coverage depth, currency, expert accessibility, linkage richness, and decay risk — surfaced as actionable intelligence for knowledge strategy decisions.
Connects to all enterprise knowledge repositories — SharePoint, Confluence, Notion, Google Drive, internal wikis, LMS content libraries, and external databases — indexing and graphing them into a unified knowledge layer without migration.
Role-based knowledge access controls, content governance workflows, audit trails for knowledge usage, expert validation tracking, and compliance-ready reporting — ensuring knowledge is not just accessible but appropriately governed.
This is what opens when a risk analyst searches for knowledge on credit risk. Not a list of 400 files. An intelligence-curated response that includes the documents, the experts, and the context — in under 1 second.
The traditional enterprise search returns a list. Horizon returns a knowledge context — ranked by relevance, annotated with currency scores, and enriched with the human expertise that surrounds each document. Speed and intelligence together.
The Climate Risk Overlay result was not in the query. The graph traversal engine surfaced it because climate risk is topologically adjacent to MSME credit scoring in the knowledge graph. This is the serendipitous discovery that no keyword search could ever return.
Every search result carries a knowledge currency score — Fresh, Current, Ageing, or Critical. A user seeing "Needs Review" knows immediately to cross-reference before relying on it. Context prevents costly decisions on stale knowledge.
Horizon does not just say "here is an expert." It says "here is Dr. Ramesh, here is why he is matched to your exact query, here are his 14 validated contributions in this domain, and here is what to discuss." The conversation starts better.
Every person in an organisation has a different relationship with knowledge — some own it, some seek it, some need to preserve it, some need to find it quickly to do their job well. Horizon serves all four.
"I manage 14 knowledge repositories, a wiki nobody uses, and a SharePoint graveyard. I have no idea what is current, what is stale, and what we have already lost."
"My team spends hours searching for SOPs, regulatory guidance, and precedent decisions. Half the time they find something outdated and do not know it. Decisions get made on stale data."
"Every time a senior person leaves, we lose 10–20 years of institutional knowledge overnight. We do exit interviews but nothing is ever captured in a way that is actually findable afterward."
"I am new. I do not know what I do not know. I spend half my day asking colleagues basic questions because I cannot find documentation — or I find something but am not sure if it is current."
When the right knowledge reaches the right person at the right moment in Astraal LXP, SkillSphere, or Xperience — that moment is powered by Horizon. And every interaction that generates new knowledge flows back into the graph to make it richer.
Astraal Horizon is measured on three outcomes: how fast people find the right knowledge, how much institutional knowledge is preserved against departure and decay, and whether that intelligence meaningfully improves the quality of decisions made with it.
A large insurance conglomerate was managing knowledge across 6 business lines — general insurance, life, health, reinsurance, investments, and distribution — in 14 separate repositories with no cross-linking, no currency monitoring, and no expertise map. A critical regulatory change in motor insurance had been documented in one repository but never surfaced to the underwriting teams who needed it — resulting in three months of non-compliant underwriting decisions before the gap was discovered. After deploying Astraal Horizon, the Knowledge Horizon Engine™ indexed all 14 repositories, constructed a 40,000+ node knowledge graph in six weeks, identified 2,400 knowledge nodes in critical decay, and surfaced 78 previously invisible subject matter experts. The same regulatory alert would now have reached 340 relevant team members within 47 minutes of ingestion.
Book a 45-minute Knowledge Health Audit — not a product demo. We will connect to one of your existing knowledge repositories, run the Knowledge Horizon Engine™ across a sample domain, and show you the currency health, expertise map, and top 5 knowledge gaps we find — live, before you commit to anything.
Run a Knowledge Health Audit →