Service S.02 · Enterprise Agentic AI · Autonomous Workflows
We build agents that plan and execute multi-step work across your CRM, ERP, and databases: reading context, taking bounded actions, and stopping for a human yes wherever the stakes are high.
30 minutes · an engineer, not a salesperson
The problem · 01
Inquiries sit in queues. Follow-ups slip. Data moves between systems by copy-paste. Rule-based automation helps until conditions change. Then it breaks, and an engineer gets paged.
Agents cover the middle ground: work that follows a goal, not a script. An agent reads the context, chooses the next step, executes it through your existing systems, and hands off to a person the moment a decision carries real risk.
What agents take over
Agent catalog · 02
Each agent owns a bounded slice of work, with its own tools, permissions, and escalation rules. Start with one. Add more as trust builds.
Resolves tickets end-to-end: reads the history, checks order status, drafts or sends the response, and escalates when confidence drops.
Qualifies inbound leads, drafts personalized outreach, and books meetings, writing every touch back to the CRM as it goes.
Watches pipelines and queues, reconciles data between systems, and files the recurring reports nobody wants to build by hand.
Processes invoices and expenses against policy, flags anomalies, and routes anything unusual to a human for approval.
Screens applications against your criteria, coordinates interviews, and answers policy questions from your own documents.
A workflow the catalog doesn't cover. We design the agent, its tools, and its guardrails around your specific process.
How it works · 03 · 4 STEPS
No agent touches production until it has passed evaluation against your real historical cases.
We map the workflow, the systems it touches, and the decisions inside it, then define exactly what the agent may and may not do.
Tools, permissions, approval points, and success metrics are specified on paper before any code. You sign off on the boundaries.
We build the agent and run it against a suite of real past cases, measuring accuracy and escalation behavior before go-live.
Shipped with logging, dashboards, and an incident runbook. Autonomy widens only as the evals prove it should.
Integrations · 04
Agents act through APIs, webhooks, and native connectors. No rip-and-replace.
Oversight · 05
Every agent ships with the controls your security team will ask about, because they will ask.
High-stakes actions (refunds over a threshold, outbound messages, record changes) pause for a human yes. You set the thresholds; the agent respects them.
Every read, decision, and action is logged with its reasoning. When someone asks why the agent did something, there is an answer on file.
Agents are measured against real historical cases before deployment, and keep being measured as models, prompts, and your data change.
Spending caps, rate limits, and scoped credentials bound the blast radius. When the agent is unsure, it flags uncertainty instead of guessing.
FAQ · 04
Get started · 30 MIN
A free 30-minute technical consultation: your goals, your constraints, and a straight answer on whether AI is worth it for your case.
Prefer email? info@euforic.io
No commitment. No deck. Just engineering.