Silverpond provides comprehensive training and change management to support successful enterprise adoption of Highlighter. Training includes role-specific onboarding, interactive workshops and tailored documentation for both technical and non-technical users. Ongoing guidance and support help organisations maximise long-term value from the Highlighter platform.

Highlighter is designed to be intuitive for operations teams while remaining powerful for software engineers. Users can configure workflows, manage data and review insights through a no-code interface, while developers can extend the platform using integrations, automation and custom code. Guided workflows and in-platform training help teams become productive quickly while providing the flexibility to support complex enterprise requirements.

Yes. Highlighter is designed for both operational teams and technical users. Business users can configure workflows, review AI assessments and manage day-to-day operations through an intuitive no-code interface, while software engineers can extend the platform using APIs, automation and custom code. This enables organisations to adopt enterprise AI without requiring every user to have technical expertise.

Highlighter enables collaboration between humans and AI through a human-in-the-loop workflow. Users can review, correct and approve AI predictions, improving model performance over time while maintaining traceability for every decision. This ensures alignment with operational standards, governance requirements and regulatory obligations.

The recommended starting point is a structured three to four-month pilot program. Each pilot includes defined success criteria, implementation support and a clear pathway to operational deployment across the enterprise. Register to See Enterprise Perception in Action to discuss your organisation's requirements and explore an appropriate pilot approach.

Highlighter can typically be operational within weeks. Rapid model training, no-code configuration and enterprise integration accelerate deployment while reducing implementation effort.

Most enterprise teams complete onboarding within two to four weeks. The timeframe depends on the complexity of the use case, system integrations and organisational requirements.

Human-in-the-loop AI means people remain in control of reviewing, validating and refining AI outputs. In Highlighter, this approach strengthens governance, improves model performance and maintains accountability for operational decisions. Users can configure detection types, schema tags and workflows through a visual interface without scripting or engineering expertise.

Highlighter enables organisations to collect, process and assess data from images, video, LiDAR, documents and sensors within a single platform. Users can configure workflows, manage AI, and trigger actions or enterprise integrations from one connected operational environment.

Highlighter is developed and supported by Silverpond, an Australian AI company specialising in enterprise AI solutions. Silverpond's in-house AI engineering and customer success teams provide implementation, platform development and ongoing technical support to enterprise customers.

Highlighter includes ongoing enterprise support throughout the customer lifecycle. This includes regular software updates, responsive technical support and proactive platform monitoring to help maintain performance, reliability and security.

Highlighter is supported by an enterprise-grade Service Level Agreement (SLA). Delivered by the team at Silverpond, the SLA includes defined uptime commitments, support response times, software maintenance, security updates and ongoing AI lifecycle support.

Highlighter's roadmap focuses on continually expanding enterprise perception through platform innovation. Future development includes enhanced IoT and LiDAR integration, faster analytics, greater compliance customisation and broader access to AI agents, making enterprise AI increasingly flexible, scalable and accessible.

You retain ownership of your data when using Highlighter. Annotations, assessments, media and metadata can be exported at any time in structured formats including JSON, CSV and Avro. Where applicable, trained AI artefacts, such as object detection or classification models, can also be downloaded, ensuring your data and AI assets remain under your control.