AI you can trust to actually understand your business

ChatGPT is a general-purpose assistant trained on broad public data. These agents are built on your organization's internal material and shaped around how you work. They use your documents, transcripts, and policies as their source of truth, and they show where answers come from so they can be checked.

Internal search platforms focus on helping people find and summarize information across systems. These agents focus on interpretation and application. They learn how your organization reasons, applies standards, and weighs evidence, then use that context to produce analysis, answers, and assets that go beyond search or summarization alone.

Much of what makes organisations work isn't written down - it's tacit expertise held by key people. We use structured interviews, voice agents, and targeted capture sessions to surface this knowledge and integrate it into your context layer. This is especially valuable where gaps are identified in existing documentation.

Trust is designed into the system. We identify trusted sources and ground truth within your organization, then map messier material back to those standards. Outputs surface their sources, highlight uncertainty or assumptions, and make it clear how conclusions were reached so users can inspect and validate them.

The system is designed to recognize when information is incomplete, ambiguous, or based on assumptions. Instead of filling gaps with confident guesses, it highlights uncertainty, shows partial evidence, or flags areas that may require human review.

Not all internal material is treated equally. The system takes into account context such as recency, source type, and relevance, and can surface conflicting information rather than silently merging it. Where appropriate, it can prompt subject-matter experts to review or resolve ambiguity.

Yes. They are designed specifically for real-world internal material, including drafts, emails, transcripts, scanned documents, slide decks, and mixed-quality sources. Messiness is expected and handled explicitly.

Each system is built specifically for your organization, and security requirements are designed in from the start. We work with you to understand your data sensitivity, governance needs, and risk profile, then design an architecture that fits - from secure cloud deployments with strict access controls to private or local model deployments where data must not leave your environment. Internal material is never used to train public models.

Yes. Evaluation isn't limited to systems we build. If you've invested in off-the-shelf AI tools, we can assess how reliably they perform against your internal standards and use cases. This helps you understand where those tools can be trusted, where they fall short, and whether the gaps are worth addressing.

No. They're designed to support expert work, not replace it. The agents handle the heavy lifting - synthesis, retrieval, and consistent application of standards - so your people can focus on judgment, decision-making, and the high-stakes interpretation where human expertise matters most.