Dedicated Execution Runtime
Your personal agent is deployed on a separate private server environment for your team. No shared runtime and no single account for all clients.
Value: privacy, control, and predictable performance.
chat-first aso for mobile apps
A Personal ASOA Agent in Your Chat
We deploy a claw-like agent for your team on a dedicated private server, connect your MCP credentials, and move Apple Search Ads analytics and automation into a chat-first workflow.
No constant work across 5-7 dashboards. No manual exports. No context loss across teammates.
one entry point for app growth
for analytics, decisions, and execution
dedicated private server
an isolated runtime per client
agintic chat app
managed through mobile chat
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What You Pay For
Integration of Your MCP Credentials
We connect your tokens and access rights to the MCP servers and ad data sources that are actually needed for your operations.
Value: a production-ready setup from day one, not a platform "for later".
ChatOps for ASO and ASA
Instead of navigating multiple dashboards all day, you give a command in chat: the agent collects metrics, explains anomalies, and proposes the next best step.
Value: more decisions, less operational routine.
Campaign Automation
We set up workflows: daily digests, alert rules, KPI checks, recommendations, and repeatable actions based on your playbooks.
Value: steady optimization pace without 24/7 manual supervision.
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Why This Dramatically Simplifies Operations
Current State
With aso.network
Business Outcome
Reports are assembled manually across multiple dashboards
One chat request returns a full summary and priorities
Your team spends fewer hours on routine operations
Reaction to KPI drops is delayed
The agent monitors KPIs and sends automatic alerts
Issues are caught before budget leakage accelerates
Decisions are fragmented across chats and spreadsheets
Decision history and actions stay in one timeline
More transparency and less duplicated work
Hard to scale process across new geos and apps
Automation templates scale to the full app portfolio
Growth without proportional headcount growth
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How Day-to-Day Work Looks in Chat
Show where ASA CPI increased over the last 7 days and suggest the 3 highest-impact actions.
I found 2 campaigns with CPI growth above 18%. Main reason: expanded broad traffic in the US and UK.
Suggested actions: 1) reduce broad ad group bid by 12%, 2) add negative keywords,
3) reallocate 20% of budget to exact ad groups with stronger ROAS.
Apply actions 1 and 2. Move action 3 to tomorrow's plan and send control metrics in the morning.
Done. Changes are applied in the runtime. Tomorrow at 09:00 I will send CPI, TTR, CR, and spend delta.
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How We Launch in a Short Cycle
Define the Runtime
We align goals, KPIs, security rules, and the list of connected data sources.
Deploy Private Server and Agent
We set up the dedicated runtime and connect MCP servers using your credentials.
Configure Scenarios
We add automations and validate them on your real ASA campaigns.
Switch Team to Chat Mode
We deliver ready command templates to get analytics and trigger actions fast.
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Pricing
Consultation
$300 one-time
BookPay as you go (No VPS)
$15+ / month
Flexible usage-based plan without a dedicated VPS. Best for lightweight workloads, testing, and teams that want to start small and scale by consumption.
Service Subscription
$500 / month
Dedicated chat-first runtime operations: ongoing automation, monitoring, and hands-on support for repeatable campaign improvements. Onboarding consultation included.
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FAQ
Where are my credentials stored?
In your dedicated private server runtime. Access is used only for approved integrations.
Can we operate without constantly logging into ad dashboards?
Yes. The core operational loop moves into chat, so dashboard use becomes occasional.
Who controls final campaign actions?
You define the policy: where actions are automated and where explicit chat approval is required.
If your team spends too much time in interfaces, it is time for chat-first ASO/ASA
In the demo, we show how your current process moves into an isolated chat runtime with clear unit economics and fast optimization loops.