Capture and automate expertise
The tacit knowledge that lives in experts’ heads
Experts
Automate and scale your expertise: advanced knowledge work
Amplify your and your team’s productivity and value
Reduce cognitive drudgery
Teams
Remove delays and bottlenecks
Elicit, share and preserve previously inaccessible institutional knowledge
Manage knowledge risk, upskilling and succession planning
A team’s most valuable asset is it’s best people and how they think… however:
Can’t scale expertise
Knowledge work and critical decisions rely on a few experts, creating delays and bottlenecks within teams
Experts become overwhelmed, constrained, and frustrated performing low-level routine cognitive tasks better suited for machines
Can’t access expertise
Tacit knowledge lives in experts’ head and not in the data
Critical risk for teams when experts are unavailable or leave
Needed to support upskilling and succession planning
Why existing AI platforms fail
Difficult to elicit tacit knowledge if not done in the right way because expertise (know-how) becomes so routine that experts apply it automatically without thinking about the steps they are taking
Expertise is a complex cognitive procedural graph comprising human judgement, reasoning, and decision heavy workflows driven by motives, goals and intentions, and not just simple linear tasks
Rely on Forward Deployed Engineers (FDE) to elicit tacit knowledge manually, which is not scalable or practical given the diverse and dynamic nature of expertise within teams
Can’t capture expertise
Can’t automate expertise
Large Language Models (LLMs) can’t reason; are too unpredictable and unexplainable; use ‘skills’ that are too simplistic; and don’t have access to tacit knowledge in its training data, prompts or context
Low-code tools are suited for simple tasks, and not designed to elicit and represent tacit knowledge which are complex cognitive procedures
Ontology, knowledge graphs and context graphs (company brain) represent facts, and not graphs that represent cognitive procedure for doing the work
Employee tracking tools capture behavioral data (what people do), not cognitive data (why, decisions) needed for advanced knowledge work
The first AI agent platform that captures and automates expertise: tacit knowledge
Non-technical experts teach AI agents how they think
Based on cognitive science and defense tech
Guided human-agent interaction captures how experts think and do their work, including what they do, why they do it, and how they do it
Eliciting tacit knowledge is like teaching a new hire
Cognitive Workflows represent & automate expertise
Cognitive workflow is a procedural graph based on the human cognitive model, designed for reasoning and complex cognitive tasks, and is interpretable by non-technical experts
Executed by AI agents to automate advanced knowledge work
Explainable, predictable and auditable so experts can reliably deploy AI agents they can trust
The Cognitive Layer for how your team thinks
New System of Record (SoR) for expertise data
Where expertise lives to support knowledge work automation and knowledge management
Teams can create, update, reuse, share, test, debug, audit and execute cognitive workflows
Operationalizing and standardizing how your team thinks
Why it matters
Preserve tacit institutional knowledge to reduce risk and support upskilling and succession planning
Automate and scale expertise to remove team bottlenecks and delays
Help experts automate what they want, exactly how they like to do it, making their work easier and faster, amplify their productivity, and thus make them and their team more valuable
About
Founder & CEO
Don Perugini has a PhD and 20+ years of experience in AI agents and cognitive science.
He has founded and exited multiple global AI agent companies in the US and Australia.
