Consulting Services

The RoakMap Framework

  • Conduct a content audit to evaluate existing digital assets, repositories, governance policies, and workflows. For AI agents, this step ensures that foundational content is clean, centralized, and free of contradictions.

    Interview stakeholders to uncover business goals, pain points, and technical needs, especially around AI use cases like automated support, personalization, or intelligent search.

    Assess compliance requirements to prevent AI from surfacing restricted or outdated information. Identify gaps, redundancies, and inefficiencies that could confuse or mislead AI systems.

  • Establish a governance model with standards for metadata, taxonomy, permissions, security, and content lifecycle. These standards are critical for AI agents to interpret content accurately and deliver consistent responses.

    Develop workflows that streamline approvals and enable cross-functional collaboration across CMS, DAM, CRM, and other platforms ensuring content is interoperable and accessible to AI tools for training, retrieval, and response generation.

  • Recommend CMS/DAM solutions that align with your organization’s maturity and AI ambitions. Prioritize platforms that support structured content, tagging automation, and integration with AI frameworks.

    Build automation for content creation, classification, publishing, and archiving to reduce manual effort and improve consistency.

    Enable AI-powered search and personalization features to enhance user experience, whether through chatbots, virtual assistants, or recommendation engines.

  • Monitor content effectiveness using KPIs and dashboards to continuously refine content processes with data-driven insights and optimize how AI agents interact with users. Track metrics like content engagement, query success rate, and resolution accuracy.

    Ensure your infrastructure is flexible enough to support emerging technologies like generative AI and machine learning so your content ecosystem can evolve alongside your AI capabilities.

  • Curate training programs and managed services to maintain system health and drive innovation.

    Educate teams on how AI agents consume and interpret content, and empower them to contribute structured, high-quality inputs.

    Establish cadence for regular updates and enhancements to ensure your knowledge base remains a reliable source of truth for AI tools, and a seamless experience for users.

Business Solutions

Sales Enablement Digital Content

  • Establish and maintain strategic alignment between Go-To-Market and sales strategies by treating content libraries not just as a resource but as a foundation for AI enablement. Regularly assess and adjust the content within the libraries to ensure it supports the evolving GTM and sales objectives.

  • Enhance visibility and retrieval of content by integrating library locations into the existing digital ecosystem. For AI agents, seamless access to centralized, well-tagged content improves response accuracy and reduces friction in automated workflows. Effectively communicate the locations of content libraries so teams and AI tools know where to find content.

  • Provide onboarding materials with clear instructions to utilize content libraries. Simplify the onboarding process to facilitate quick adoption and engagement with available resources.

  • Aim to improve the seller experience by addressing not only sales but also revenue enablement to drive performance. Implement feedback mechanisms to continuously refine the seller journey and content effectiveness.

  • Create a seamless connection to readiness materials and training opportunities in GTM and sales tools. Ensure sellers have immediate access to necessary educational resources to enhance their skills and knowledge.

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Knowledge Base & Content Libraries

  • Strategically organize and store a diverse array of digital content tailored for marketing, sales enablement, and various organizational functions. Ensure the content is structured in a user-friendly manner, facilitating easy access and utility for the intended audience. To support AI agents and tools, ensure content is structured in a machine-readable format—using consistent metadata, modular layouts, and standardized terminology.

  • Sustain a content library that resonates with the organization’s objectives, meticulously curated to prevent the accumulation of superfluous material. A lean, well-maintained library improves AI performance by reducing false positives, minimizing outdated references, and streamlining response accuracy.

  • Develop a uniform set of attributes, vocabularies, and taxonomies designed to enhance content discoverability for users and for AI agents as well. This systematization enables both humans and machines to locate precise, contextually relevant content quickly and reliably.

  • Oversee the entire content lifecycle, encompassing the stages of creation, storage, and eventual archiving or disposal. This ensures the content repository remains up-to-date and pertinent and reduces the risk of AI surfacing obsolete or conflicting information.

  • Foster a collaborative environment for content creators, editors, and publishers. Align their efforts within a digital workspace that is conducive to efficient workflow processes and collective productivity.

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