AI execution your agency can trust

AI proposes. A named human decides. AI executes. The record compounds.

Start a four-week pilot See the orchestrator

The Orchestrator

Marketing doesn’t need another copilot. It needs the layer above the stack.

Deep Order sits above the tools a team already uses — Google Ads, Meta, GA4, the CMS, Slack, the CRM — and turns campaign data into a single queue of evidence-backed proposals. Copilots draft and stop. The orchestrator owns the decision, the approval, and the measured outcome.

88%

of organisations use AI in at least one business function

McKinsey State of AI, 2025

~6%

see 5%+ of EBIT attributable to AI

McKinsey State of AI, 2025

95%

of enterprise AI pilots show no measurable P&L impact

MIT NANDA, 2025

Everyone is testing. Almost nobody is banking the value.

Approval queue

One prioritised queue of evidence-backed actions

Pending work surfaces as cards — each with the evidence and the recommended change. A named owner approves, rejects, amends, or routes client review. Publishing stays human-controlled.

What compounds underneath

Context Vault

Brand rules, tone, personas, playbooks, and credentials travel with every workflow — agents never work from a blank prompt.

Creative Genome

Per-client memory of what that audience rewards — hooks, angles, visual patterns, fatigue — learned from results, not guesses.

Decision record

Evidence, owner, rationale, action, and measured result — one exportable unit that compounds with every approval.

AI + human collaboration

Five stages. One load-bearing decision.

Every action passes through the same governed loop — what separates Deep Order from automation that acts without asking, and from copilots that ask without acting.

  1. Signals + context

    Campaign data, brand rules, and prior decisions are pulled together.

  2. Recommend

    An evidence-backed action is proposed, with the reasoning attached.

  3. Load-bearing

    Decide

    An Expert Lens challenges the proposal first. Then a named owner approves, rejects, or amends — with reasons recorded.

  4. Act

    A channel-ready instruction is executed; publishing stays human-controlled.

  5. Learn

    The outcome writes back into decision memory — so the next run starts smarter.

AI creates. Experts challenge. Humans approve.

Deep Order — Run #47 audit trail
09:02

Data Analyst pulled GA4 + Google Ads performance

Describe the work. Get a governed workflow.

Natural-language authoring becomes agents, data sources, and approval routes — scheduled, measured, and ready on day one. 94 marketing-specific nodes. 225 templates.

Deep Order runs workflows like weekly budget optimisation

Start a four-week pilot

Review & delivery nodes are first-class — governance ships native, not bolted on.

225 workflow templates, live on day one
94 marketing-specific builder nodes
12 review & delivery nodes built in

System of action

It doesn’t replace your tools — it coordinates

One governed unit per decision

Evidence, owner, rationale, and measured result — spanning paid media, creative, SEO/GEO, and reporting without forcing the rest of the stack to change.

  • Not a copilot — owns decision, approval, execution, and outcome.
  • Not generic automation — marketing agents, templates, and playbooks ship in.
  • Expert lenses — challenge recommendations before a human sees them.
  • Compounding defence — Genome + decision record improve with every approval.

Fig. 1 Deep Order coordinates decisions across the marketing stack

Analytics & data

GA4 · Search Console · DataForSEO

Ad platforms

Google · Meta · TikTok · LinkedIn

Content & CMS

CMS · Figma · asset libraries

CRM & comms

CRM · Slack · email

Project tools

Tasks · docs · knowledge bases

Governance

Approval-native — the layer clients and procurement care about

Approvals are built into the architecture, not bolted on. Materiality thresholds route client review where required. The audit trail records what each agent did, what data it used, what it produced, and who approved it.

  1. Human-controlled Nothing publishes without a named approver; publishing stays in the team’s hands.
  2. Your data stays yours Owned and exportable at any time, no lock-in — Deep Order never trains on client data.
  3. Full audit trail Every decision records who decided, why, and the result — the artefact procurement asks for.
  4. AI-use disclosure Clients can see exactly where AI assisted, on the policy thresholds the team sets.

Approval-native design has cleared enterprise procurement review at two anchors — built for named owners, audit trails, and AI-use disclosure from the start.

Prove it on your own book — in four weeks.

Three governed workflows on your stack, with your approvals and success criteria agreed up front. Your team decides throughout. No lock-in.

Email hello@deeporder.ai

The three workflows

  1. Weekly paid-media budget optimisation — Google, Meta, TikTok, and LinkedIn by ROAS and client priorities
  2. SEO/GEO visibility & competitor monitoring — hero categories across Google and AI search
  3. Campaign launch approval workflow — brief to approved channel assets, governed

Success criteria

  • Hours saved per week
  • Approved actions shipped
  • Campaign changes live
  • Reporting time reduced
  • Learnings captured in playbooks

Illustrative agency model: ≈$880K capacity freed and ≈$500K new revenue potential — rebuilt with your book in the pilot before any decision to scale.