Custom AI · Senior team · 100% remote delivery

AI built into your business.
Not bolted on.

Off-the-shelf SaaS bends your team around the software. We do the opposite — learn how your business actually runs, then ship custom AI wired into your data and workflows. Senior engineers, remote from day one. Outcomes, not seat licenses.

See engagement models
Embedded

We learn your team, data, and process the way a senior hire would — not as a vendor passing through.

Remote

No travel days, no on-site theatre. Same depth as an embedded team, delivered over Slack, Linear, and code.

Outcomes

We get paid when work ships and metrics move — not for seats, recurring SaaS fees, or hours billed.

How we build
Five steps. No deck-ware.

The reason custom AI usually fails is process — not models. We borrow the embedded delivery model that works in defense and high-stakes industry, strip out the on-site theatre, and ship.

01

Map your operations.

We sit with the people doing the work — sales, ops, finance, support — and build a precise model of how decisions actually get made today. Not the wiki version. The real one.

02

Find the leverage points.

Where is judgment repeated? Where do humans copy data between five systems? Where do good decisions wait on slow ones? Those are where AI earns its keep.

03

Build on your data.

We wire models into your CRM, your warehouse, your ticketing system, your SharePoint. The AI sees what your team sees — and writes back where it should.

04

Ship in weeks.

First working version live in 4–6 weeks, not 9 months. Real users, real workflows, measurable lift. Iterate from there.

05

Hand it over — or run it for you.

You can take ownership of the code and models on day 1. Or we keep operating it for you. Either way, no lock-in, no surprise renewals.

What we build
The work that pays for itself.

These are the patterns that show up across customers. Yours will look different in the details — but the shape rhymes.

AI agents for ops

  • Inbound lead scoring + routing
  • Claims triage and pre-adjudication
  • Procurement and invoice review
  • Tier-1 support resolution

Decision support

  • Underwriting copilots
  • Clinical chart summarization
  • Sales briefings from CRM + calls
  • Forecast and anomaly surfacing

Knowledge + retrieval

  • Search across SharePoint, Drive, ticketing
  • Policy + SOP assistants
  • Compliance audit trails
  • Onboarding agents

Workflow automation

  • Multi-system data reconciliation
  • Report and deck generation
  • Vendor and contract intake
  • Custom internal tools
4–6w
to a working v1
first real users, real workflows
100%
remote delivery
no travel days, no on-site theatre
1
team you hear from
senior engineers, not an SDR layer
0
seat licenses
you own the code and the models
Why remote
The embedded model,
without the airport.

The reason embedded delivery wins is depth — engineers who actually understand the customer's operations. The reason it stays expensive is logistics: hotels, flights, badge access, week-long travel cycles. We kept the depth. We dropped the travel.

Lower cost
No T&E line item. No premium for senior people willing to live out of a suitcase. The savings go into more engineering, not more travel.
Faster ramp
Day-1 access via your existing tools — Slack, Linear, GitHub, your data warehouse. No NDA-then-badge-then-VPN dance.
More senior people
Our engineers don't move cities for engagements. That means we can put deeper experience on smaller projects than an on-site model can.
Always-on record
Decisions live in writing in shared channels and docs. New people onboard from the trail, not from a war story.
Engagement models
Two ways to start.

Pick the one that matches the risk you're comfortable taking. Most teams start with Discovery and graduate from there.

Discovery
Two weeks. Find the leverage.
$25kfixed
Two-week engagement
  • Operations mapping with your team
  • Top-3 AI leverage points, ranked by payback
  • Working prototype on real data
  • Build-vs-buy recommendation for each
  • Optional follow-on, no obligation
Most common
Build
One workflow. Shipped to users.
Typically 6–10 weeks
  • Custom AI for a single high-value workflow
  • Wired into your data and existing systems
  • Live with real users at the end
  • Measurement baked in from day one
  • Code + models handed over, your IP
FAQ

Common questions.

Why remote and not on-site?

The depth of an embedded model comes from access to your people, data, and tools — not from being in the same building. Modern collaboration tools make that access trivial. Travel adds cost and slows the work down without making it better.

How is this different from a typical consultancy?

We ship working software, not slide decks. Engagements end with code, models, and live workflows in your environment — not a recommendation. We're also fixed-scope by default, so a Discovery is $25k whether it takes ten days or fifteen.

Whose IP is the AI we build?

Yours. From day one. Code, prompts, models, fine-tunes, data pipelines — all written to your repos, your accounts, your environment. We don't put your workflows behind a proprietary platform you can't leave.

What about security and compliance?

Engagements run inside your perimeter — your cloud, your VPN, your SSO. We sign your MSA, your DPA, and your security questionnaire. For regulated workflows (healthcare, finance, public sector), we'll build to the framework you already operate in.

Do you compete with our internal team or our incumbent vendor?

Neither. We work the way good contractors do — under your tech leadership, alongside whoever's already there. If we're still here a year in, it's because the work compounds, not because there's lock-in.

Tell us the workflow.
We'll tell you what to build.

A 30-minute call with a senior engineer or partner. No deck, no SDR, no follow-up sequence.

hello@cocolevio.com