Aimash / Hermes — Google Ads operations in Telegram
A Google Ads assistant for account managers and agencies: inspect performance, prepare reports and review campaign changes in Telegram. Hermes selects the tools; every write needs one human approval and a checked result.
Try the interactive demoTimeline
2026
Role
Lead Engineer
4
Workflow stages
1
trusted approval per change
RU · EN
Chat languages
Engineering outcome
Chat-based reporting and changes with one approval
Honest impact
An inspectable workflow: read → propose → approve → verify
Interactive product demo
From a message to a verified change
Explore three everyday Google Ads workflows. Read a report, review a budget proposal, or cancel it before anything changes.
Interactive illustration with fictional accounts and sample figures. This page is not connected to Telegram or Google Ads; it does not show client performance results.
Aimash · Hermes
Demo · sample data
You
Increase the daily budget for Search · Demo from €50 to €60.
First, let the assistant prepare a proposal. You will be able to approve or cancel it.
Reports you can take away
Account analysis, period comparisons and spreadsheet exports for further work.
Ad copy ready for review
Generate search-ad headlines and descriptions, validate their limits and review a proposal before publishing.
Follow-up after a change
For supported changes, a read-only outcome checker compares later metrics. It does not autonomously adjust the account.
Under the hood: where the control lives
Telegram → Hermes Gateway → typed MCP tools → PostgreSQL proposal and trusted approval → Google Ads execution → audit and readback. Identity, freshness checks and one-time execution are enforced in Python, outside the model.
This case describes the implementation in the Aimash repository, reviewed in September 2026. A website demo is an illustration of that workflow, not a live production test or proof of revenue growth.
Have a workflow like this?
Start with one repetitive task: reporting, reviewing changes or connecting an internal system. We define the inputs, approval rules and a result you can verify before expanding the scope.
Discuss an automation pilotProblem
Account managers spend time moving between campaign screens, spreadsheets and client conversations. Delegating changes to AI raises a separate question: who controls the target account and the money being changed?
The Challenge
Turn a plain-language request into useful Ads work while keeping account identity, the exact before-and-after change and approval under explicit control. A fluent answer must not be mistaken for a completed action.
The Solution
Hermes handles the conversation and selects typed MCP tools. Python reads Google Ads and stores a concrete proposal in PostgreSQL. A trusted Telegram approval authorizes one execution; the system records the action and reads the result back. Reporting and follow-up checks can run without changing the account.
Technical Highlights
Typed tools separate account reads, planning and approved actions.
Immutable proposals bind the target and before-and-after values to a trusted Telegram decision.
One-time execution guards prevent a repeated callback from applying the same proposal twice.
Freshness checks stop execution when the account state no longer matches the proposal.
Audit and Google Ads readback determine the result; generated text is not the source of truth.
Supported changes have a read-only outcome check; no client revenue uplift is claimed.
System Architecture
Python 3.12 · Hermes Agent + trusted Telegram transport
openai-codex (role-based model routing)
Google Ads API v25 (GAQL + guarded mutations)
Typed MCP tools for READ, proposals and approved execution
SQLAlchemy + Alembic + PostgreSQL
Pydantic tool schemas (function calling)
Hermes cron + read-only outcome scheduler
openpyxl + Google Sheets API
Fernet-encrypted secrets · audit log
Docker + GitHub Actions CI (ruff · mypy · pytest)
Core Technologies
Related Projects
Have a process that should run as a safe AI system?
I turn complex workflows into a scoped pilot with typed tools, approval gates and verifiable outcomes. You work directly with the engineer who builds and deploys it.