AgentDock

1.7k

Every decision, backed by a reason you can see.

Most AI support answers and forgets. AgentDock runs a decision system: policies, signals, precedents, and guardrails resolve into every answer, and the reasoning is recorded. Ask what would happen before it acts; read why it acted after.

Four inputs. One decision.

Every answer is a decision, not a guess. Your policies set the frame, the live signals weigh what matters now, the closest precedents say what worked before, and the guardrails draw the line it cannot cross. The agent resolves all four into one move, on every conversation at once.

How it decides
  • PoliciesNo discount below list price
  • SignalsReads as expansion-ready
  • Precedents11 of 12 like it grew
  • GuardrailsInside your approval limits
Decision

Offer the annual care plan at list price.

$36,000/ year

Booked at full value, no discount given away.

New case · renewal at risk
Matching against resolved cases…
  • Mid-market renewal, same plan94% matchRenewed
  • At-risk account, 3 years in88% matchSaved
  • Downgrade reversed with a plan swap81% matchRenewed
$12,400retained

It reasons from cases like yours, not from scratch.

Every case your team resolves becomes a precedent, weighted by who decided it and how it turned out. When a similar one arrives, the agent pulls the closest matches and reasons from them, so it can act on the handful of cases that worked before instead of guessing. Every case your team closes is one more the next decision can stand on.

Ask what happens before it acts.

Before you change a policy or approve an offer, ask the hypothetical. The agent reasons from 9 similar accounts and forecasts the likely result, so you are deciding from your own track record. Test it against your history before it ever meets a real customer.

Ask “what if?”

“What happens if we offer this account the annual plan?”

Forecasting from 9 similar accounts...
78%
likely to accept
$18,000
revenue at stake
Annual plan
best next move

What that looks like on a real conversation.

Guardrails

The limits it can never cross.

Hard boundaries enforced at the moment of action, not suggested in a prompt: discount ceilings, compliance rules, refunds past a window, words it will never say. Before your AI runs a tool or sends a reply, the action is checked against your guardrails. If it would cross one, your AI does not do it quietly, it blocks the action or hands the case to a person, and the check is recorded either way.

Enterprise renewal$40,000 / yr

“Give us 50% off or we walk.”

Your AI is about to act…
Apply 50% discountBlocked
Offered 20% and an annual plan$40,000held at full value
On the record

Every decision kept, with the reasoning intact.

When your AI answers, the answer and the why are recorded together: the context it read, the signals it weighed, the precedent it matched, the guardrails it checked. That record is the system of record for your decisions. When something goes wrong you fix the rule instead of guessing, when a customer disputes what happened you have the account, and when an auditor asks you open it instead of reconstructing it.

Recommended the annual care plan
Why, on the record
ContextLoyal customer, 3 years, 2nd repair booked
SignalsUpsell-ready, low churn risk
PrecedentMatched annual care-plan case, 91%
GuardrailsWithin discount and compliance limits
On the record, auditableDecision #4821

Frequently Asked Questions

Decisions you can stand behind.

One AI handles every customer on a decision system you can read, and every decision is recorded with the reasoning behind it. Your team steps in only when it counts.

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