How does Linkence protect sensitive enterprise data?

Security is built into every layer. Linkence uses end-to-end encryption at rest and in transit. Role-based access controls ensure users only see documents they are authorized to access. Enterprise customers can deploy in their own VPC or on-premise infrastructure.

What AI models can we use with Linkence?

Linkence supports 15+ LLM providers including OpenAI, Anthropic Claude, Google Gemini, Mistral, Cohere, and more. You can also connect to Azure OpenAI, AWS Bedrock, or self-hosted solutions like Ollama. Bring your own API keys and switch models anytime with no vendor lock-in.

Which tools does Linkence integrate with?

Linkence integrates with 50+ popular tools including Gmail, Slack, Notion, Jira, Confluence, Google Drive, Salesforce, HubSpot, Zendesk, GitHub, and more. Custom API connectors are also supported for internal systems.

How long does Linkence implementation take?

Most teams are up and running in under a week. Initial connector setup takes minutes, access control configuration can be done in hours, and rollout to teams happens in days. Enterprise deployments with custom requirements typically take 2-4 weeks.

What authentication methods does Linkence support?

Linkence supports enterprise-grade authentication methods including email/password, passwordless OTP, Google OAuth, Microsoft OAuth, Azure Active Directory, and generic OAuth/OIDC for providers like Okta and Auth0. Just-in-time provisioning auto-creates accounts on first login.

Can Linkence be deployed on-premise or in a VPC?

Yes. Enterprise customers can choose VPC deployment in their cloud account or fully on-premise installation. Linkence supports AWS, GCP, and Azure with flexible deployment models to meet security and compliance requirements.

Use case

Engineering knowledge search across repos, issues, pull requests, and wikis

Help engineers understand how systems work by searching repository docs, pull requests, issues, Jira tickets, Confluence specs, Slack incident channels, and Teams discussions from one AI Chat surface.

Natural language search for engineering context

Search intent includes engineering knowledge search, GitHub AI assistant, Jira AI assistant, Confluence AI search, pull request summary, and incident summary AI. LINKENCE is built for teams whose decisions live across tickets, repository docs, PR discussions, wiki pages, and chat.

GitHub and Bitbucket supply readable repository documentation, issues, pull requests, and review context. Jira supplies execution state. Confluence stores agreed design. Slack and Teams often hold incident decisions. AI Chat fuses them with hybrid retrieval so keywords and natural language both help.

Safe engineering actions

Actions can prepare Jira updates, channel status notes, or repository-related follow ups with approval. That gives engineering teams workflow support without turning every chat prompt into an unreviewed write.

Common workflows

Summarize incidents and releases

Combine channel messages, Jira work, Confluence runbooks, and pull request context into a timeline or release-risk summary.

Find architecture decisions

Ask why a system behaves a certain way and retrieve the Confluence page, PR discussion, or Jira ticket that explains it.

Prepare Jira follow ups

Use Actions to draft issue updates or follow up tasks from chat context, with approval before writes.

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