Shared business context
Connect records into a versioned business model that supplies common entities, rules, and decision rights to agents.
Enterprise AI agents for processing business records and carrying out policy-controlled workflows.
Avataar is an enterprise AI workflow platform built around a shared model of a business, its records, rules, and decision rights. Connect information such as contracts, claims, records, promotions, and logs, then use task-specialized models and agents to assess cases against rules and evidence and prepare updates, alerts, or summaries in connected systems.
Implementation begins with mapping a workflow, its data sources, owners, risks, and current baseline. Avataar’s team designs and deploys the system with the organization; customer teams can then add workflows through a registry and retain the platform and operating model. Deployment and model routing need to be agreed with the organization, with approval, policy, and human-review controls configured before agents act.
Connect records into a versioned business model that supplies common entities, rules, and decision rights to agents.
Read from connected systems of record and carry out enabled updates in those systems, subject to configured permissions and policies.
Use models selected for the task and business data. Architecture work evaluates where smaller models or API-based models fit the workload.
Check cases against business rules, earlier decisions, and supporting evidence, then produce reasoning, approvals, updates, alerts, and summaries.
Apply access controls, policy checks, audit history, model evaluation, and monitoring for drift, cost, latency, and escalation.
After deployment, customer teams add workflows through the registry and reuse the shared business context and governance.
Gather relevant business records, evaluate them against agreed rules and evidence, and send uncertain cases for human review.
Turn a reviewed decision into an authorized system update, alert, or summary with an audit trail.
Map owners, data, decision rights, and the current baseline before deploying a first workflow and assessing its result.
Add another workflow to the registry while reusing the organization’s data model and controls.
Bring a workflow, the systems it touches, its current cost or baseline, and its owner to a scoping session. The implementation process then maps use cases and decision rights, designs the architecture, and deploys agreed workflows.
Deployment options include an on-premises data center or the organization’s own AWS, Azure, or GCP tenancy. Confirm model routing, data residency, and operating requirements for the selected architecture.
Yes, through connected read-and-write workflows. Agent actions are policy-gated and depend on configured access, decision rights, approval thresholds, and human-review controls. Validate the workflow before relying on its actions.
Customer teams retain the operating model, platform, and governed workflows. They can add workflows through the registry, with governance and shared business context continuing across agents.
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