01↗
Knowledge, connected.
Retrieve relevant company knowledge with RAG, so answers can be grounded in the documents and context behind them.
RAG · CONTEXT · SOURCE EVIDENCETHE VEKTORAX PLATFORM
One connected workspace.
Many better next steps.
Vektorax is building a unified AI layer for business operations. Connect company knowledge, understand operational data and coordinate work in one product experience.
● ● ●vektorax / product concept◇
KNOWLEDGE WORKSPACEILLUSTRATIVE PREVIEW
Answers with context. Not guesswork.
⌕What is holding up the supplier onboarding process?
Context-led response
The example checklist is waiting on supplier documentation. Review the missing tax details and the purchasing team’s approval before moving forward.
Supplier checklist2 documents awaiting review
↗Purchasing handbookApproval guidelines · section 4
↗Suggested next step · approval requiredDraft a follow-up for review
→WORKFLOW WORKSPACEILLUSTRATIVE PREVIEW
From repeatable work to repeatable flow.
⌕Prepare a follow-up for the pending onboarding request.
Context-led response
A follow-up draft can ask the supplier for the outstanding documents, reference the checklist and route the message to the purchasing team before sending.
Pending requestExample supplier · onboarding
↗Communication policyExternal messages need approval
↗Illustrative workflow · nothing is sentReview the proposed workflow
→ANALYSIS WORKSPACEILLUSTRATIVE PREVIEW
Find the signal behind the spreadsheet.
⌕Where should we investigate delays this month?
Context-led response
In this example, document review is the recurring handoff to investigate. Compare completion dates and review the underlying records before deciding on a process change.
Operations summaryIllustrative review dataset
↗Process definitionOnboarding stages and owners
↗Example analysis · not a measured outcomeExplore the supporting evidence
→Interactive interface concept with fictional sample data. Not a live platform, integration or performance demonstration.
ONE PRODUCT. CONNECTED CAPABILITIES.
Less switching.
More understanding.
The product is designed to combine contextual knowledge, analysis and automation rather than make teams assemble separate AI tools.
02↗
Workflows, without the busywork.
Bring repeatable tasks into structured flows. Use AI agents to propose and coordinate next steps with appropriate human review.
AI AGENTS · APPROVALS · AUTOMATION03↗
Operations, understood.
Use machine learning and language models to explore operational data, surface patterns and support informed decisions.
ANALYSIS · PATTERNS · DECISIONSPRODUCT DEVELOPMENT
Built with teams.
Not just for them.
We’re working toward early access. The interface above illustrates our direction; it is not a production application.
What early conversations help shape
Which company knowledge is hardest to find. Which tasks repeat across teams. Where approvals stall. What evidence people need before trusting a recommendation.
What to expect
A discussion about your workflow, current tools and data needs. Features, integrations, availability and deployment options will be confirmed directly—not assumed from a concept preview.
Discuss your workflowBUILD WITH INTENTION
Your operations.
A more intelligent next chapter.
Tell us where work gets stuck. Help shape what comes next.