Any agent
Any stack
One clean data layer

From framework to production in three steps

Connect once, ask in plain English, and your agent keeps everything your team taught it - on whatever framework you build with.

1

Connect

SETUP

Connect your agent to Improvado once - secure access is granted at onboarding, no keys pasted into your code.

[Google Ads] [Meta Ads] [HubSpot] [GA4] [] [] [] []

8 of 1,000+one governed layeryour agent

PII masked · SOC 2 Type II · EU residency

Set up once at onboarding - nothing for your team to install or maintain.

2

Ask anything

ASK

Your agent pulls from any connected source in one ask - no per-platform integrations to build or maintain.

Scan all our accounts for spend anomalies overnight.

Scanned 52 accounts · flagged 3 anomalies. Biggest: US-Search-Brand, +38.4% spend.

Pause the worst one.

Paused it - reversible, fully logged, ~$92K protected this month.

412 ms median answer · every number source-cited · saved to shared memory

A live answer from your connected data.

3

It remembers

MEMORY

Your agent keeps long-term memory - it saves what it learns and recalls it in every later run, shared across your team.

Long-term memoryalways on

• CAC target $410set by your team
• Your naminglearned on run 1
• Past findings52 accounts watched

recalled in every later run, shared across your agents

Saved to your team's shared memory.

# 1 - Show setup command
{
  "mcpServers": {
    "improvado": {
      "url": "https://mcp.improvado.io/v1"
    }
  }
}
# 2 - See the request
POST /v1/query  { agent, scope: "all_accounts" }
200 OK  52 accounts scanned  3 anomalies
top: US-Search-Brand  +38.4% spend
$ status: ok  latency 340ms
# 3 - See whats stored
mcp.memory.write("cac_target", $410)
recalled next run  persisted across sessions
graph: 214 nodes  shared across agents
$ status: ok  ttl 30d

Show me what a custom agent does for spend anomalies

One connection to all your data - pick a use case to see what a custom agent delivers.

The data layer every custom agent needs

Skip the integration grind - your agent gets every channel, clean and governed, on day one.

Minutes to your first answer, not a data project

Point any agent framework at Improvado and it reads your live marketing data the same day - no point-to-point integrations to build or maintain.

One governed layer between your agent and your entire stack

Switch AI tools whenever you want. Your data, access rules, and team memory stay put. Click a product below to see how it connects.

# 1 - One connection, declared once
{
  "mcpServers": {
    "improvado": {
      "url": "https://mcp.improvado.io/v1",
      "auth": "oauth"
    }
  }
}
# 2 - Scopes - role-based, read-only by default
# read:spend
# read:crm
# read:attribution
# write:memory
# 3 - Shared memory - survives an agent switch
# persisted in the governed knowledge graph
# versioned
# every agent reads the same nodes

Your agent inherits the workspace policy - read-only by default, writes capped and reversible, and every decision logged with the seat that made it. every agent query logged, role-scoped, in transit and at rest - zero raw credentials.

Common questions

Everything teams ask before wiring their first custom agent to Improvado.

Building with a different agent stack?

Claude

Query your marketing stack from the Claude app your team already uses.

Data1,000+ connectors

AccessWorkspace SSO

Ask inPlain chat

View page →

OpenAI Codex

Clean spend and attribution data for your coding assistant.

DataSame clean data

AccessSecure token

Ask inNotebooks & scripts

View page → Active

[Improvado] Custom agent

Any agent framework, one clean governed data layer. You are on this page

DataAny agent framework

AccessScoped keys

Ask inYour agent framework