Wikilect
    AI coworker for enterprise teams

    Connect your internal systems to secure AI workflows

    Wikilect is a controlled AI coworker platform for company teams. It combines approved knowledge sources, role-based access, and workflow orchestration so employees can produce practical outcomes: summaries, documents, reports, support responses, and operational actions.

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    Customer-controlled access

    Connected data is accessed only after explicit consent.

    Scheduling and coordination across connected calendar tools

    Knowledge search across approved internal sources

    Document drafting and summarization workflows

    CRM, support, and operations automation with human approval

    Integrations and permissions

    Each permission maps to a visible user feature

    Wikilect requests the narrowest access rights required for enabled workflows and approved integrations. Customers can disconnect integrations from the product at any time.

    Calendars and meeting systems

    Used to check availability, schedule events, and keep approved coordination workflows in sync.

    Documents and knowledge sources

    Used to access customer-approved files and portals for search, drafting, and process execution.

    Spreadsheets and reporting data

    Used to read and update approved datasets for reporting, enrichment, and operational workflows.

    CRM, support, and messaging tools

    Used only for approved communication and service workflows, including drafting, sending, and analysis.

    Role-based outcomes

    Useful across business functions, not just one department

    Beyond document search, Wikilect helps teams produce approved deliverables inside daily business workflows while preserving access boundaries for each role.

    Leadership, operations, and support

    Teams use Wikilect to prepare management summaries, run standard operating procedures, and respond faster with approved instructions and customer context.

    Marketing, sales, and customer communication

    Agents draft campaign materials, meeting prep notes, follow-up messages, and customer-facing documents using approved company sources.

    Engineering, analytics, and product teams

    Wikilect helps teams navigate architecture docs, internal APIs, metric definitions, and historical decisions to produce code, reports, and technical briefs faster.

    Implementation path

    Roll out in stages and scale what works

    Teams start with a fast onboarding phase, launch practical use cases, then expand into deeper automations and integrations based on real adoption data.

    1. Fast knowledge onboarding

    Initial company materials are connected so the agent can answer with your policies, standards, and process context from day one.

    2. Guided team launch

    Teams start with practical workflows for daily work: question answering, document preparation, reporting, and operational coordination.

    3. Expansion with integrations

    After early usage data is collected, workflows are expanded with deeper CRM, ERP, support, and service integrations for high-impact scenarios.

    Workflow orchestration

    WikiFlow adds a control layer for AI scenarios

    For organizations running multiple channels and processes, WikiFlow keeps scenario logic reusable, governable, and easier to evolve without rebuilding every integration path.

    One scenario, multiple channels

    The same automation logic can be reused across chat surfaces, webhooks, and internal entry points without rebuilding each flow from scratch.

    Centralized orchestration

    Business teams and admins manage AI logic, integrations, and transitions between steps in one controlled environment.

    Designed for complex AI workflows

    Useful when workflows require context switching, tool usage, and multi-step decision paths rather than single prompt responses.

    Deployment options

    Choose the environment that matches policy requirements

    Wikilect supports both rapid cloud rollout and strict on-premise deployment, so teams can balance delivery speed, governance, and infrastructure strategy.

    Cloud deployment

    Fastest time to value for teams that want quick rollout, minimal infrastructure overhead, and elastic scaling.

    On-premise deployment

    Preferred by organizations that require strict data locality, internal security controls, and controlled update procedures.

    Frequently asked questions

    What is Wikilect?

    Wikilect is an AI coworker for business teams. It connects approved company sources — calendars, documents, spreadsheets, CRM and support tools — to AI workflows for scheduling, knowledge search, document drafting and customer operations.

    Which company data does Wikilect access?

    Only the sources a customer explicitly connects and approves: calendars and meeting systems, documents and knowledge sources, spreadsheets and reporting data, and CRM, support and messaging tools. Access is scoped to the workflows the customer enables.

    Do agents act without human approval?

    No. Customers review and approve workflows that send messages, create or modify documents, update spreadsheets, schedule meetings or perform other actions through connected accounts.

    How is Google user data protected?

    Wikilect protects OAuth tokens and customer data used in AI workflows, uses secure transport for communication with Google APIs and customer-facing services, and expects customer data and integration secrets to be protected at rest with appropriate technical and organizational controls.

    How can a customer disconnect the integration and delete stored data?

    Users and customers can disconnect Google access and request deletion of stored data at any time. When an integration is disconnected, stored refresh tokens are deleted or disabled and the app stops using Google APIs for that account. Access can also be revoked directly in Google Account security settings.

    Can Wikilect run on our own infrastructure?

    Yes. Cloud deployment gives the fastest time to value with minimal infrastructure overhead and elastic scaling; on-premise deployment suits organizations that require strict data locality, internal security controls and controlled update procedures.