Knowledge Engine for People & HR

Run people operations from one trusted workforce picture.

Connect workforce data, policies, approvals, and employee workflows to improve planning, service, and compliance.

KEP

Workforce operations review

Review onboarding readiness for next month’s hires and flag anything that could delay day one.

I connected accepted offers, start dates, manager tasks, equipment, access requests, policy steps, and training assignments. I’m preparing the readiness brief now.

New-hire readiness briefReport

58%

lower token cost

when using Knowledge Engine

2x

more tasks

vs. frontier models

32%

more accurate with open source

vs frontier model

19 of 34

tacit-knowledge facts captured

vs. RAG’s 1

Source: “Knowledge Engine Platform for Long-Horizon Professional Agents” and “Context Graphs for Recovering Tacit Organizational Knowledge”, Accrete AI, August 2026.

The employee journey crosses systems, policies, and owners.

Headcount, recruiting, compensation, onboarding, performance, learning, access, and compliance rarely share one operating view. People teams spend too much time reconciling data and chasing handoffs, then still have to explain the result to leaders.

People & HR cognitive fabric

Connect the context behind the work.

Agents learn the language of the work, create the data flows that connect its systems, and build a living context graph for each request.

Agents learn your language

They learn your teams’ terms, shorthand, and ways of working, then create a shared understanding of what everything means.

Agents connect your systems

They create the data flows that bring the right information together for each task, without manual setup for every source.

Agents build the context graph

They connect people, records, decisions, and outcomes while preserving a clear path back to the source.

From domain language and source data to a context graphThe context model resolves jargon, synonyms, abbreviations, and intent into shared entities and relationships. Source mappings connect those concepts to tables and keys while agentic data pipelines prepare durable data. The resulting context graph can be virtualized over its sources or materialized.NATURAL-LANGUAGE REQUEST“What could delaynext month’s hires?”CONTEXT MODELDomain languageJARGON · SYNONYMS · INTENTREQ→open rolestart→first workdayintent: check readinessCanonical modelENTITIES · RELATIONSHIPSCandidateHireAccessFILLSNEEDSSemantic bindingsCONCEPT → SOURCE DATACandidate→GreenhouseHire→WorkdayAccess→Oktatables · columns · keysAGENTIC DATA PIPELINESCONTEXT GRAPHGreenhouseWorkdayOktaCandidatesHiresAccessJOINOnboarding contextAlex MorganHIREAug 12STARTLaptopACCESSIT OpsOWNERVIRTUALIZEDquery sources in placeMATERIALIZEDpersist selected subgraphs
The context model interprets a domain’s vocabulary, synonyms, abbreviations, and intents, then resolves natural-language requests to shared entities and relationships. Source mappings connect those concepts to tables, columns, keys, dialects, and execution integrations. KEP can query the resulting context graph virtually over source data or materialize selected graph data.
  • Workday
  • Greenhouse
  • BambooHR
  • Microsoft 365
  • Google Workspace
  • Slack

Workflows

Change the work, not just the interface.

01

Plan the workforce with shared data

Connect headcount, openings, budget, capacity, attrition, and organization context to prepare scenarios and leadership-ready workforce reporting.

02

Coordinate employee lifecycle work

Track onboarding, offboarding, approvals, access, equipment, training, and manager actions with clear owners and policy gates.

03

Deliver policy and people service

Retrieve approved policy context, prepare responses and case summaries, and surface recurring issues without exposing information outside the requester’s permissions.

One end-to-end example

From accepted offer to a ready, governed first day.

  1. 01

    Connect

    Gather the accepted offer, start date, manager plan, HR tasks, access and equipment requests, required policies, and training assignments.

  2. 02

    Analyze

    Check dependencies, deadlines, owners, access scope, and missing information against the organization’s approved onboarding process.

  3. 03

    Deliver

    Create the readiness brief, owner checklist, employee communications, and status view for People, IT, and the manager.

  4. 04

    Control

    Respect employee-data permissions and require authorized human review for employment, compensation, access, or policy decisions.

What the team gets

Outcomes people can inspect and use.

Workforce planning brief

Headcount, openings, capacity, cost, risk, assumptions, and scenarios prepared for leadership review.

Lifecycle readiness view

Onboarding and offboarding tasks, owners, dependencies, deadlines, and approved status communications.

Policy and service brief

Source-linked policy context, case summary, open questions, and a proposed response for authorized review.

The Accrete product

Context, work, and control in one path.

The Knowledge Engine coordinates sensitive people workflows across approved systems while preserving source permissions and keeping consequential employment decisions with authorized people.

Start with one workflow

Define the outcome before expanding the system.

Bring the workflow, its information sources, its approval requirements, and the result your team needs. We’ll map a focused first deployment and the path to reuse.

Discuss this workflow