Pricing built around value delivered,
not seats billed.

Based on agent usage and deployment complexity, not per-seat. You pay for what you use, and costs scale with the value you receive.

Yes. Start with one department for as little as a single workflow. Most customers begin with their highest-cost process, averaging $180,000 in annual manual labor, and see full payback before expanding.

Cloud, private cloud, on-premise, hybrid, and VPC, all with pricing that adapts to your infrastructure requirements.

We offer a guided pilot with fixed scope and explicit success criteria. The average pilot delivers $45,000 in measurable value within 30 days, making the decision to scale self-evident.

4 weeks for a production pilot, 8–12 weeks for full department-wide deployment. We have never exceeded 16 weeks for even the most complex enterprise rollouts.

Zero data retention. Your enterprise data is never used for model training. Data stays in your environment, we enforce least-privilege access and full audit logging across every deployment.

Every agent operates within configurable guardrails, confidence thresholds, and escalation rules. When an agent encounters uncertainty, it escalates to a human, never guesses. Current production accuracy across deployments: 97%.

Yes. assistents is model-agnostic. Deploy with Amazon Bedrock, Azure OpenAI, Google Vertex AI, or self-hosted models. Switch providers without re-engineering your agents.

Custom-built AI agents typically take 12–18 months to reach production-grade reliability. assistents delivers production agents in 4 weeks, battle-tested with governance, audit trails, and compliance built in from day one.