AI Suite - AI Agent Training
Your AI agent is making mistakes.
We fix that in 7 days.
Retrained on your real data, tuned for fewer hallucinations, faster resolutions, and escalation logic that actually works. EN+ES.
The Problem
Your AI agent launched well.
Then it started making expensive mistakes.
Hallucinations on edge cases - the agent confidently gives wrong answers on your own policies
Escalation rate climbing - more and more conversations landing on your human team
Accuracy degrades over time as your products, prices, and policies change
You have no systematic way to retrain - fixes are one-off patches that don't hold
What We Do
Systematic retraining.
Not one-off patches.
Conversation audit and failure mapping
We pull your last 90 days of conversations, tag every failure mode, and map the root cause for each error type.
Knowledge base refresh
Your current policies, products, and procedures are re-ingested. Outdated information replaced. Knowledge gaps filled.
Prompt engineering and tuning
System prompt, few-shot examples, and instruction layers rebuilt to eliminate the top 5 failure patterns from the audit.
Escalation logic rebuilt
We re-engineer the escalation triggers based on real failure data - not guesses. The agent now knows exactly when to hand off.
Regression testing suite
300+ test cases run against the retrained agent before it goes live. Every previously failing case must pass.
Monthly retraining retainer option
Ongoing subscription to keep the agent current as your business changes. New policies, new products, new edge cases covered.
Real Results
What changes after
a proper retraining cycle.
Error rate reduction average
Measured across the top 5 failure modes identified in the audit. Tracked against baseline.
Retraining cycle duration
Audit, fix, test, and redeploy in 7 days. No extended downtime, no big-bang replacements.
Escalation rate drop
Fewer conversations reaching your human team because the agent resolves more correctly.
Knowledge currency window
We refresh your agent's knowledge base every 90 days so accuracy doesn't drift as your business changes.
Who This Is For
Any business running an AI agent
that isn't performing.
E-commerce with high return rates
Healthcare with complex triage logic
Financial services with compliance needs
SaaS with evolving product docs
Agencies managing client agents
Any business post-AI-launch plateau
The Process
Audit, fix, test,
redeploy. 7 days.
Conversation audit
We analyze 90 days of conversations, classify every failure mode, and rank by frequency and business impact.
Knowledge refresh
Policies, products, and procedures re-ingested. Knowledge gaps from the audit filled with accurate data.
Retrain and test
Prompt rebuilt, 300+ regression tests run. Agent must pass all previously failing cases before promotion.
Redeploy and monitor
Retrained agent goes live. We monitor error rate, escalation rate, and CSAT for 30 days post-launch.
FAQ
What clients ask
before retraining starts.
Yes, if we have access to the conversation logs, the current knowledge base, and the deployment environment. We've retrained agents built on OpenAI, Anthropic, and most major platforms.
We define baseline metrics before retraining (error rate, escalation rate, resolution time) and measure the same metrics post-launch. You see the before/after in a report.
Our regression suite tests all currently-passing cases before we promote the retrained agent. We do not deploy if any previously working behavior degrades.
Depends on how fast your business changes. Quarterly is the minimum for most businesses. High-velocity businesses (new products monthly, frequent policy changes) benefit from monthly cycles.
Monthly knowledge refresh, one full prompt review per quarter, and access to our Slack channel for flagging new failure cases as they emerge.
Your agent is better than this.
Let's prove it in 7 days.
Audit, retrain, redeploy. EN+ES.