AI for data and operations

Your cloud data costs too much and moves too slow.

Both fixable in weeks — not quarters.

We know the bill no one can explain — and the dashboard everyone is waiting on. If you run on Google BigQuery and Looker, we reduce that cost 30–60%, measured on your own bill, not a slide. The repetitive reporting moves to AI that works alongside your team. On your existing stack.

For CEOs and data leads who no longer trust the cloud bill — or the dashboards.

Typical reduction

30–60% Cost 80% Manual work Manual With agents

Typical client outcomes — your range comes from the audit.

The edge · 01

We don't use AI. We run on it.

Agents do the work. Humans curate, decide, review. When a client asks for a proposal, four agents coordinate and a human PM signs off — what takes two days elsewhere takes two hours here. The infrastructure we run on is the infrastructure we ship.

Read the manifesto →
Sales Finance Operations Support Human PM

Four agents coordinate; a human PM signs off. Representative — our studio runs 21.

What we do · 02

One studio. Three units. Built on the stack you already have.

Your cloud data, without next month's shock bill.

(Google BigQuery + Looker)

That bill nobody can fully explain — we've been on the other side of it. We cut BigQuery cost 30–60% in 6–8 weeks, measured on your own billing, and take the ad-hoc reporting off your team.

−30 to 60% BigQuery cost
Explore Data & Analytics →

The busywork off your team. Your people back to real work.

Billing, collections, recruiting, support, reporting — the repetitive load your team never chose. AI takes it on and works alongside them: same team, more throughput, fewer errors.

up to −80% manual load
Explore Agentic Workforce →

Products live and working today.

notarIA, CoreWhapp, LKMind, DataMetricX. Plug into your stack in hours, not a project.

4 products hours to connect
Explore Products →
The numbers · 04

Same team. More capacity. We earn every claim with a number.

−30 to 60%

BigQuery cost, in 6–8 weeks

+60%

faster dashboard load times

−60 to 80%

time-to-hire with recruiting agents

40 to 70%

support ticket deflection

up to −80%

manual admin load

21

specialized agents running our own studio

Measured on the client's own billing. Not on ours.

The agents take the repetitive load. The people move up to the work only a person can do.

Client proof

What clients say about our work

Real reviews from Looker & BigQuery engagements — verified on Upwork and LinkedIn.

  • 100% Job Success
  • 6,300+ hours delivered
  • 9 completed engagements
  • Identity verified Upwork

Testimonials shown in their original language.

Free assessment · 03

Your team is doing work an agent could take.

In about 15 minutes we map 3 to 5 processes in your operation — billing, collections, WhatsApp and support, reporting, CV screening — where an agent can take the repetitive load off your people. We don't touch what already works, and we don't replace anyone: the agent handles the busywork, your team moves up to judgment work. You see the number first.

If there's no fit, we'll tell you — and you owe us nothing.

up to −80% of the manual load — 3 to 5 processes an agent can take this month

15 minutes. Zero commitment. If there's no fit, we'll tell you.

We operate on your stack — we don't migrate or replace what already works. Read-only where it counts, encrypted, never used to train models.

manual hours / week after agents →

15-minute mapping. The repetitive load an agent can take, surfaced upfront.

The RavenCoreX team at work
Who we are · 06

Two founders. 21 agents.

Talent from LATAM. Delivery to US standard. Same time zone as the US East Coast. The infrastructure we run on is the infrastructure we ship.

We use the same agents to take the busywork off our own people — so they rise to the work that needs a human. That's exactly what we bring to your team.

Let's talk · 06

You know who we are now. Let's talk about you.

30 minutes. No pitch. We bring a number, you bring your stack. If it doesn't make sense, neither of us wasted any time.