An AI agent inside your business.

Analyzes your data. Builds your automations.

Lives in your Slack channel. Knows your business — and learns more every week. Drop in a question, get an answer back. Drop in a workflow, get an automation built. We run the agent; you get the work done.

From $3.5K/mo

Plugs into the stack you already run

BigQuerySnowflakeShopifyKlaviyoMeta AdsGoogle AdsGA4SlackGorgias

What it does

What's included every month

One agent, two modes — analytics and automation. Six concrete deliverables every month, plus continuous learning under the hood.

Weekly insight digest

Every Monday: a 5-bullet summary + Loom video covering what moved last week and why.

Monthly board-ready review

A clean deck or doc with KPIs, trends, anomalies, and three recommended actions.

Ad-hoc tasks in Slack

Drop in a question or a build request — get an answer or an automation back within four business hours on weekdays.

One major build per month

A new dashboard, an internal automation, a pipeline, or a tool — built natively in your existing stack.

10 hours of engineering work per month

Pipelines, automations, integrations, internal tools. Overage at $150/hr with a live Slack-visible meter — no surprise invoices.

Continuous knowledge-graph maintenance

Every entity, transformation, and quirk gets captured so the agent compounds in value over time.

Try it out

What can I have it do?

Real Slack messages an operator could send their AI agent. The analytical asks come back with charts, the underlying SQL, and links to the source data. The build asks come back with a working automation.

?

What are my sales today vs the same day last week?

Daily ops
?

Are refunds spiking on any SKU this week? If yes, why?

Daily ops
?

Build me a Slack bot that pings the ops channel any time a SKU's refund rate jumps more than 2x its weekly baseline.

Build
?

Go through Reddit and TikTok, see what people are saying about my brand and my top three competitors this month, and send me a report.

Customer
?

Which of my Meta creatives are showing fatigue? Surface ones with CTR down >15% week-over-week.

Marketing
?

Set up a daily 8am email to me with yesterday's sales, inventory health, and any anomalies you spotted overnight.

Build
?

Pull a cohort LTV chart for customers acquired in the last 6 months, split by acquisition channel.

Marketing
?

Cluster last month's support tickets into the top five themes and tell me what changed vs the prior month.

Customer
?

Add a workflow that pulls new Stripe payouts into my finance Google Sheet automatically, with categorisation.

Build
?

Prep a slide for the board meeting on the three biggest things that moved this quarter.

Strategic

Slack is the default interface. Email digests, custom dashboards, or direct CLI access work too.

The cadence

Connect → Learn → Compound

If you already have a warehouse, you're getting insights in week 3. If you don't, we build it for you — the agent learns your business during the build, so by go-live it already knows your data intimately.

Full breakdown

Week 1

Connect

We connect the agent to your warehouse and surrounding tools via MCP — BigQuery or Snowflake, Shopify, ad platforms, Klaviyo, Slack, whatever you use. Read-only by default.

Week 2

Learn

The agent builds a knowledge graph of every important table, dashboard, and quirk. We sit with you for 2–3 sessions to seed the context only you have.

Week 3+

Compound

First weekly insight digest goes out. Slack channel open. Every question, analysis, and quirk gets written back to the knowledge graph — and the agent gets faster and sharper every week.

The moat

What sets us apart

One agent that does both the analytics and the engineering, and remembers your business between sessions. Most "AI for your company" tools forget everything past the conversation; ours builds a persistent, self-extending knowledge graph that a competitor can't replicate in a weekend.

Glean / Hebbia / enterprise AI search

They do · Help you find a document or answer a factual question

We do · Run analyses, build dashboards, ship automations, write code

Fractional analyst firms (Chameleon, Pineapple)

They do · Senior humans on retainer — no AI layer, billed hourly

We do · AI-native delivery: 3–5× the work per dollar, and the agent learns your business each week

AI automation agencies (n8n / Lindy shops)

They do · Stitch one-off workflows; no analytical depth, no persistent context

We do · Same agent does the analysis and the automation — and remembers your business between sessions

Hiring an analyst + a developer in-house

They do · Two hires, 60-day search each, easily $8–15K/mo combined in the UAE

We do · One agent + a fractional human layer, live in week 3, from $3.5K/mo

Pricing

One number, no menu paralysis

Onboarding (~30 hours) included in month one. Intro pricing live for our first three clients.

Early Adopter Discount

AI Agent Retainer

One agent. Analytics and automation. Fully managed.

$6,000$3,500/mo

Save $2,500/mo

Standard $6K/mo rate kicks in once we have three case studies live.

  • Weekly insight digest
  • Monthly board-ready review
  • Ad-hoc tasks in Slack
  • One major build per month
  • 10 hours of engineering work per month
  • Continuous knowledge-graph maintenance

Term

3-month minimum, then month-to-month

Guarantee

30-day money-back guarantee on the first month

Annual prepay

~15% off if you prepay 12 months upfront (effectively 2 months free)

Bigger build, custom automation, or heavier setup? We'll walk you through options on the discovery call.

Book a 15-min call

Common questions

FAQ

Will the AI break things?
No — by architecture. Low-risk analytical work (SQL, dashboards, reports, answering questions) the agent does autonomously. High-risk, irreversible actions (deploying code, scheduling jobs, modifying live data, sending external comms) the agent only proposes. A human approves before anything runs. The agent cannot autonomously trigger writes to your production systems. This is a real architectural commitment, not a marketing line.
Is this an analyst, or an automation builder?
Both — same agent. Drop a question on Slack ("what are my refunds doing this week?"), get an analysis back. Drop a build request ("alert the team any time refunds spike on a SKU"), get a working automation back. The agent uses the same knowledge graph for both, which is why one product can credibly do two things — it knows your business, your data, and your existing tools.
How is this different from Glean or other enterprise AI?
Enterprise search tools help you find a document or answer a factual question. We run analyses, build dashboards, ship automations, write code. The compounding-knowledge moat is the bigger difference — our knowledge graph is persistent, self-extending, and gets more valuable every week. A competitor cannot rebuild 3–6 months of accumulated company-specific context in a weekend.
What if we already have an analyst or a developer?
We work alongside them, not instead of. Your humans focus on strategic work; the agent handles the manual reporting, ad-hoc questions, and small automations that eat their week. Most teams find their in-house people become more productive, not redundant.
What if our data is a mess?
That's usually the point. The knowledge graph fixes that as a side-effect — every quirk and undocumented rule gets captured the first time it comes up, and after a few weeks your data is better-documented than it has ever been.
What if we don't have a data warehouse yet?
We build it as part of onboarding. The agent participates from day one, learning your business while we design and ship the warehouse, so by go-live it already knows your data intimately. If the build is significantly bigger than the standard onboarding envelope, we discuss it transparently on the discovery call.
How long until we see insights?
Week 3 if you already have a warehouse. Weeks 5–6 if we're building it. The first weekly Loom going out on that timeline is non-negotiable.

See the agent live in 15 minutes.

Pick a slot. We'll screen-share the production deployment and answer your questions in real time.