of cloud spend delivers no value: the first rise in five years, driven by AI workloads nobody’s watching closely enough.
Source: Flexera, 2026The intelligent system that continuously understands your technology estate, and proactively tells you what to fix, save and improve.
“Who owns this, and could we prove it’s under control if someone asked right now?”
None of this shows up as a single line on a budget. It shows up everywhere, a little at a time, which is exactly why it’s so easy to ignore, and so expensive to keep ignoring.
of cloud spend delivers no value: the first rise in five years, driven by AI workloads nobody’s watching closely enough.
Source: Flexera, 2026Hours, not seconds. “Who owns this? What depends on it? Can we safely change it?” Instant questions that still mean meetings and manual digging.
Whoever knows, leaves. Ownership and architecture knowledge live in people’s heads. When they go, so does the only working map of your stack.
Compliance, wherever it applies. DORA, NIS2, SOC2, ISO 27001, PCI-DSS or your own standard. The audit always starts with a question your systems can’t answer alone.
None of this was possible five years ago. All of it is table stakes now. The only question is whether you build it, or buy it already working.
Modern APIs expose nearly everything about your systems, in real time. The data was always there, waiting to be connected.
Graph technology has matured enough to model, query, version and reason over genuinely complex enterprise relationships.
Capable enough now to investigate, correlate, summarize, recommend and validate, and to keep learning, across an entire estate.
People now expect to ask their technology landscape a question in plain language, and get a grounded answer.
Each one owns a slice.
Manually maintained, not real-time
Hard to keep current, infrastructure-only
Engineering-only, no compliance view
Runtime-focused, no business context
One provider at a time, no enterprise-wide view
An intelligent enterprise system built on a living, versioned knowledge graph. Unlike a graph you have to query, it doesn’t wait to be asked. It continuously discovers what’s changed across your estate, reasons across every connected system, and tells the right person what to fix, save or improve before they think to look.
From scattered systems to a single, evidenced picture, and from that picture to action.
Nine enterprise system families, read-only by default.
Scheduled jobs pull reality continuously, not once.
Heterogeneous data mapped to one common model.
Every relationship versioned, traceable, evidenced.
Role-aware insight, compliance auditing, cited answers.
Discovery is read-only by default and runs on a schedule, not on trust. Every write back (a pull request, a ticket, generated documentation) is reviewed and approved by a human first.
Six roles. Six different questions asked of the same graph, at the same time, with no synchronization required.
See use casesEvery control gap and piece of evidence, current continuously, not just when an audit is scheduled.
For youTechnology risk
See exactly what a change touches before you ship it, and what broke before anyone opens a ticket.
For youNew & changed dependencies
A living map of the estate that’s never more than one discovery cycle out of date.
For youArchitecture drift detected
Know what’s blocking a release and who owns the fix, without a status meeting.
For youOwnerless critical service
Idle, oversized and orphaned cloud resources, surfaced automatically with the owning team already tagged.
For youCloud optimization opportunity
One place to ask any question about the stack, and get an answered, evidenced response.
For youModernization opportunities
Discovery is read-only by default and runs on a schedule, not on trust. Every write back (a pull request, a ticket, generated documentation) is reviewed and approved by a human first.
The same discovery, knowledge graph and Co-Pilot power every use case below. Only the question changes.
DORA posture audited continuously, remediated as code, opened as a reviewable pull request.
See it live →Design files, docs, wiki pages and call transcripts become a validated backlog, sent to Jira.
See it live →Docs and diagrams generated from the graph on demand, published to Confluence and watched for drift.
See it live →DORA, for a financial institution: one applied example of the same Compliance & Risk Intelligence capability. Swap the framework and the pattern holds: NIS2, SOC2 Type II, ISO 27001, PCI-DSS or your own internal standard.
Compliance by framework article and critical business function, movement since the last review, and exactly what’s blocking sign-off.
“23 services across 4 business domains resolve to one Oracle instance.” Architecture risk and compliance risk, in one card.
ICT third-party exposure and Register of Information completeness (DORA Art. 28–30).
“9 of 42 critical applications have no identified owner; 14 have no current documentation.”
Every finding is cited. Every fix ships as code, opened as a real pull request to the team that owns it. The framework changes. The mechanism doesn’t.
For everyone who shapes a project during discovery and analysis, and just as useful once implementation starts. Always scoped to the feature you name, never an unbounded search.
Design files, docs, wiki pages and stakeholder-call transcripts become one coherent backlog, not one story per document.
Epics and Stories as titles and one-liners, so you judge the shape of the backlog before any detail is written.
Full descriptions, testable acceptance criteria and Implementation Tasks under every Story, each field confidence-scored.
Pick the board or take the Co-Pilot’s suggestion. Access and write permission are checked first, and the credential is create-only.
Where sources disagree, the confidence score drops and the conflict is shown, never silently resolved. Every correction becomes versioned knowledge.
On demand, during Discovery or mid-implementation: architecture, infrastructure and network documentation and diagrams, published to Confluence.
Ask for an application, infrastructure or network diagram, or a narrative write-up, for anything the graph knows.
Every paragraph and every diagram node traces to a graph fact and carries a confidence score. Gaps are stated, never invented.
Inline or conversational edits, then an explicit Validate. Nothing reaches Confluence before that step.
Sent to the space and page you choose, write permission checked first, then flagged the moment the graph it came from changes.
The write credential creates and updates pages only: no deletes, no moves, no permission changes. Every publish is logged, with who validated it and who sent it.
Lagoria is deployed inside your own cloud account, in the region you choose, and nothing leaves it. The same architecture that keeps you DORA- or SOC2-ready keeps your data exactly where you put it.
Every AI model call runs inside your own account and chosen region. Your enterprise data is never sent to any AI provider, or to anyone outside your environment.
Subject to the certifications and compliance boundary your account already carries. Nothing new to audit, nothing new to trust.
Discovery is read-only by default. Where Lagoria writes back (a pull request, a ticket, generated documentation), a human reviews and approves it first, every time.
Role-based access and full audit logging on every fact, every query, every action, enforced server-side, not by policy alone.
A 10-week pilot, read-only by default and inside your own account, that ends in real, evidenced results.
Discovery read-only by default. Every write path (a pull request, a Jira ticket, generated documentation) gated at every step. Nothing lands in your systems without your own team’s review.
Agreement, sign-off, prerequisites, access provisioned.
SSO, RBAC, audit logging, connectivity waves live.
Wave 1
Wave 2
Wave 3
Entity resolution tuned past 85% accuracy, human enrichment.
A gap report against the framework or savings target that matters to you, with remediation PRs opened.
Baseline
Pilot