AI agents for ad optimisation

AI agents that optimise your ad spend — while you sleep.

Pruuv runs a team of agents against every client's goals in the background — reading real CRM outcomes, spotting waste, and staging confidence-scored recommendations you can read. Approve them, or set a confidence threshold and let them run — with guardrails, and a loop that grades its own decisions.

12 agencies
in production
£8M+
spend under management
+22%
matched revenue / 30 days
Nightly
across every platform
Meta · Ad set · Prospecting UKHIGH
92conf

Reduce budget 15%

Spend up 31% week-on-week but matched revenue flat — CPA drifting above target. Trim to protect ROAS.

How it works

One overnight cycle. Six stages.

A scheduler wakes every minute; a director agent runs the whole book nightly.

01

Observe

Pulls spend, creatives and conversions from every connected platform.

02

Analyse

Joins ad data to your funnel + CRM and grades each entity against its targets.

03

Recommend

Drafts entity-level actions with a 0–100 confidence score and plain-English reasoning.

04Key

Approve

Configurable from fully manual to confidence-based auto-approval, with approval chains for sign-off.

05

Execute

Pushes budget, bid, pause and enable changes directly to the platform.

06Key

Reflect

Measures the real KPI impact 7+ days later, feeding a win rate that makes the agents better.

Under the hood

Recommendations you can read. Guardrails you can trust.

Recommendations you can read

Every action — budget, bid, pause, enable — carries a 0–100 confidence score, one line of reasoning, and an estimated impact. Nothing is a black box.

Confidence-threshold auto-approval

Set a per-client threshold. Above it, agents act on their own; below it, a human reviews. You dial in exactly how much autonomy each client gets.

Guardrails you can trust

A stale-data skip, a daily action cap, a max budget-change cap, and a negative-trend circuit breaker keep the agents inside the lines — always.

Full autonomy, your rules

Agents execute budget, bid, pause and enable changes directly across every connected platform — gated only by your confidence threshold and guardrails.

Conversion send-back

Matched conversions are pushed back to Meta, Google, TikTok and LinkedIn, so each platform’s own optimisation learns from real revenue — not pixel proxies.

Self-improving

A master agent shadow-tests strategy changes and promotes the winners automatically, so the system gets sharper every week.

Grounded in outcomes

Agents optimise toward real revenue — not vanity metrics.

Pruuv ingests every ad platform and joins it to your funnel and CRM with per-connection attribution, showing first-click and last-click side by side. So “a conversion” means a real deal — and that's what the agents chase, against each client's targets.

Matched revenue · 7d£161,712
Last-click£128,440
First-click£192,308
Linear£160,074
Connects to your whole stack

Every ad platform. Every CRM. One substrate.

New connectors ship every couple of weeks.

Meta
Google Ads
TikTok
LinkedIn
Microsoft Ads
Customer.io
Attio
HubSpot
Salesforce
Pipedrive
Zendesk
GA4
Snowflake
Stripe
Shopify
Request a connector
Built for agencies

Every client, every spend — on one page.

A per-client-workspace agency overview that tells you which of your clients need a human today — and which are quietly compounding overnight. Sparkline rows, on/off-track target dots, and a queue of decisions instead of a queue of spreadsheets.

Leadly Digital / OverviewLast 7 days
Leads
1,847
Spend
£34.2k
CPL
£18.51
Revenue
£161k
MMis-sold Expert
£12.4k5.1×On track
NNorthRoad Homes
£8.2k3.2×Review
CCaldera Clinics
£6.7k6.4×On track
AAverly Legal
£4.1k4.8×On track
Before Pruuv, we ran 30 client reviews every Monday morning. Now the agents do it overnight — we walk in to a queue of decisions, not a queue of spreadsheets.
D
Head of Performance
Leadly Digital
+22%
matched revenue in 30 days
6h
saved per analyst / week
30
clients under management
£0.42
per agent run

See Pruuv against your own ad accounts.

Invite-only · OAuth-first · your approval rules, always