How do I cut my AI bill with one-click recommendations?
Use Cognocient's AI Advisor to find your biggest cost savings and apply them without touching your code.
Goal: Identify and apply the top cost-saving opportunities in your AI spend — without any code changes.
Time: 30 minutes to apply. Savings appear in the next billing period.
Prerequisite: At least 7 days of API calls through the Cognocient proxy so the Advisor has enough data to analyse.
Step 1 — Open AI Advisor
Go to Dashboard → AI Advisor (or click Recommendations in the sidebar).
The Advisor analyses your call patterns and ranks recommendations by estimated monthly saving. Each card shows:
- What the issue is — e.g. "chatbot uses GPT-4o for 3-token classification outputs"
- Estimated saving — e.g. "$420/month"
- Confidence — based on how many calls it's seen
- One-click apply — creates a routing rule automatically
Start with the highest-saving recommendation at the top of the list.
Step 2 — Apply the top recommendation
Click Apply on the top recommendation. You'll see a preview of what changes:
- Model downgrade — e.g. GPT-4o → GPT-4o-mini for the flagged feature
- Scope — which feature and department the rule applies to
- Estimated impact — how many calls per day will be affected
Confirm and click Apply. The routing rule is created instantly — no deployment, no code change.
How it works
Cognocient creates a routing rule that intercepts calls matching the scope and rewrites the model in the request before forwarding to the provider. Your code keeps sending gpt-4o. The proxy silently sends gpt-4o-mini. Your code sees the same response format.
Step 3 — Check the result after 48 hours
Come back to AI Advisor in 2 days. The recommendation will show:
- Actual saving so far — real dollars from calls that hit the new routing rule
- Quality signal — if you've tagged calls with
X-Cost-Outcome, the Advisor shows whether quality held up
If the feature's output quality has held up, keep the rule. If something degraded, click Revert to restore the original model — one click, no deployment.
Step 4 — Work through the list
Repeat for each remaining recommendation. Common findings:
| Finding | Typical saving |
|---|---|
| GPT-4o used for short classification outputs | 60–85% cost reduction |
| Identical prompts sent repeatedly (no caching) | 75–90% via prompt cache |
| Batch-eligible workload using real-time endpoint | 50% with Batch API |
| Context window bloating after 5 turns | 20–40% with context trimming |
If you don't see recommendations yet
The Advisor needs enough data to be confident. If your call volume is low:
- Make sure calls are going through the proxy (check Live Calls tab)
- Make sure you've added
X-Cost-Featureheaders — without them, all calls look like a single unattributed pool - Wait 7+ days for call patterns to stabilise
See Tag Your First AI Call if attribution isn't set up yet.
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Tag Your First AI Call
Add 2 headers to your existing code and see per-feature spend in under 5 minutes.
Set a Monthly Spending Limit
Create a hard budget enforced at the proxy before charges reach your provider bill.
Get Slack Alerts on Spend Spikes
Connect Slack and get notified the moment an anomaly or budget threshold is hit.