Never. We operate on a strict Zero-Trust architecture. We utilize isolated Service Accounts, OAuth2, and App Passwords. Your root infrastructure remains completely untouched.

We deploy sovereign n8n instances on isolated AWS or GCP servers. Your data never trains public LLMs, and memory vectors are strictly ring-fenced within your own cloud environment.

All endpoint credentials are AES-256 encrypted within our cryptographic vault. They are only decrypted in memory during runtime execution.

Yes. Our architectures are engineered strictly adhering to Zero-Trust frameworks and enterprise-grade security principles. We ensure your data pipelines are heavily encrypted, isolated, and fully audit-ready.

Single-node AI employees typically deploy within 24 to 48 hours following technical requirement mapping and credential handoff.

Yes. Our architecture utilizes native webhooks, REST APIs, and GraphQL to bridge directly into Salesforce, Shopify, Zendesk, Slack, and legacy databases.

We execute a 4-step protocol: Technical Audit, Provision & Configure, Adversarial Testing, and Live Deployment. You are updated at every milestone.

A description of the workflow or bottleneck you want automated, access to the relevant systems via scoped credentials rather than root access, and one point of contact for the handoff.

Our workflows are engineered with Watchdog nodes. If an endpoint drops, the system triggers exponential backoff protocols, caches the payload, and auto-retries until success.

We implement dynamic fallback routing. If an OpenAI endpoint hits a rate limit, the system seamlessly routes the query to Anthropic Claude or a localized open-source model with zero latency.

No. For high-stakes operations (invoicing, refunds, outbounding), we mandate a Human-in-the-Loop (HITL) approval queue via Slack or email before the action executes.

Workflows run inside bounded state machines with retry limits and timeout logic. If an agent cannot resolve a task after a set number of attempts, it escalates to a human instead of looping indefinitely.

Individual AI employee deployments start at $1,500. Full autonomous departmental mesh networks scale from $50,000 to $250,000+ depending on architectural complexity.

No. You are buying sovereign infrastructure, not renting software. You pay for the architectural deployment and a flat retainer for maintenance. Token costs are passed directly to you from the LLM providers at cost.

We track capital saved through reduced manual headcount, accelerated ticket resolution SLAs, and zero-latency outbound scale. ROI is typically realized within the first 45 days of deployment.

Uptime monitoring, Watchdog auto-retry handling, error resolution, and minor configuration updates.