Average enterprise time-to-productivity is 8-12 months because institutional knowledge is...
New hires productive in weeks, not months
Enterprise onboarding fails because tribal knowledge lives in the heads of tenured staff. Context builds a knowledge graph from every tool your team uses, so new hires get answers with citations from day one -- without interrupting anyone.
Book a Demo60%
REDUCTION IN TIME-TO-PRODUCTIVITY
20%
SENIOR ENGINEER TIME RECOVERED FROM REPETITIVE Q&A
5x
FASTER ACCESS TO INSTITUTIONAL KNOWLEDGE
100%
ON-PREMISE -- ONBOARDING DATA NEVER LEAVES YOUR NETWORK
The Problem
Why this is hard without a knowledge graph
Average enterprise time-to-productivity is 8-12 months because institutional knowledge is undocumented
Senior engineers spend 20% of their time answering the same onboarding questions repeatedly
New hires lack context on past decisions, leading to repeated mistakes and rework
Onboarding documentation is outdated within weeks of being written
The Solution
How Context solves it
01
Self-service knowledge from day one
New hires query across Confluence, Slack, Jira, and every internal tool to find answers with citations. No more waiting for the right person to be available.
02
Decision trail visibility
Every architectural decision, process change, and strategic pivot is traceable. New team members understand not just what was decided, but why.
03
Living documentation that stays current
Context's knowledge graph updates as your tools update. New hires always get the latest information, not a stale wiki page from 18 months ago.
04
On-premise means onboarding data stays private
Employee queries, org charts, and internal processes never leave your infrastructure. Safe for classified environments and regulated industries.
Beforeraw signals
Senior engineers spend 20% of their time answering the same...
New hires lack context on past decisions, leading to repeated...
Onboarding documentation is outdated within weeks of being written
Average enterprise time-to-productivity is 8-12 months because institutional knowledge is...
Senior engineers spend 20% of their time answering the same...
New hires lack context on past decisions, leading to repeated...
Onboarding documentation is outdated within weeks of being written
Afterstructured outcomes
01
Self-service knowledge from day one
02
Decision trail visibility
03
Living documentation that stays current
04
On-premise means onboarding data stays private
How It Works
From deployment to answers
01
Connect your tools
Helm install into your VPC. Connect Confluence, Slack, Jira, SharePoint, and other knowledge sources in minutes.
02
Knowledge graph builds automatically
Context extracts entities, relationships, and provenance from every document, thread, and ticket. No manual tagging required.
03
New hire asks a question
"Why did we choose Kafka over RabbitMQ?" -- Context returns the original decision thread, the ADR, and the people involved.
04
Answer with citations
Every response includes source links, timestamps, and authorship. New hires can verify and dig deeper.
05
Knowledge compounds
Every query strengthens the graph. Onboarding gets faster for each subsequent hire as institutional memory grows.
FAQ
Frequently asked questions
How does Context help with employee onboarding?
Context builds a knowledge graph from your existing tools (Confluence, Slack, Jira, etc.) so new hires can ask questions and get citation-backed answers from day one. Instead of waiting for a senior colleague to be available, they get self-service access to institutional knowledge.
How long does it take to deploy Context for onboarding?
Most deployments are production-ready within 2-4 weeks. Context connects to your existing tools via standard APIs and builds the knowledge graph automatically -- no manual tagging or content migration required.
Can Context replace our existing onboarding documentation?
Context complements your existing documentation by making it discoverable and connecting it to related decisions, discussions, and context. It surfaces the right document at the right time, even if that document lives in Slack, Jira, or email.
Is onboarding data safe with Context?
Context deploys entirely on your infrastructure -- on-premise, VPC, or air-gapped. Employee queries, org structures, and internal processes never leave your network. No data is used for model training.
How does Context handle outdated documentation?
Context's knowledge graph is temporal -- it tracks when information was created, modified, and by whom. When answers reference older content, Context flags the recency and surfaces newer related information automatically.
What ROI can we expect from AI-powered onboarding?
Enterprise customers typically see 60% reduction in time-to-productivity and 20% recovery of senior engineer time previously spent answering repetitive questions. The 30-day proof-of-value pilot measures these metrics in your environment.
Industries
Industries that benefit most
See Context in action
30-minute technical walkthrough. No slides -- just a live demo tailored to your environment and use case.
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