Where does your work break down? And do you even need AI to fix it?
AntlerWing is the AI-multiplied operating partner for companies that have bought the systems and need them to actually run. We bring AI in where it multiplies, and tell you when it does not. Senior engineers leading. No decks, no phase-one-of-seven.
Partnerships
- monday.com Platinum
- Make
- Cerri Platinum
- Odoo
- PartnerView Platinum
Built. Live. Measurable.
Three operating models we shipped that did the real lift inside the customer's business. The numbers are theirs, not ours.
Scoped as 20 hours for one team. Internal demand pulled it to 63 operators in 90 days. Nobody upsold it.
A Fortune 500 fintech with a hard contract deadline and a claims library that was a legal liability if the audit trail broke. We re-architected it with an AI layer that catches bad claims before legal sees them.
600+ client boards rebuilt from the ground up, live on the target date, and now the reference call monday.com makes to close other deals.
Built by people who've been in your seat.
Every senior operator on our team came from inside a company like yours. We've been the head of operations, the head of finance, the CTO, the founder. We've watched monday.com adoption stall. We've sat through eighteen-month ERP slips. We've shipped AI that worked and AI that didn't. We know what breaks because we used to be the ones it broke for. Now we do this work for companies still in those seats.
Meet the teamIf AI is the right move, we run the whole thing.
Most teams know AI matters. Far fewer know where it belongs in their business, which use case to start with, or what it looks like in production six months in. We are the guides for that. We find the value, build it, deploy it, and stay until the team is using it.
- Find the value
Map where AI multiplies and where it does not.
Two to three weeks of operator-led diagnostic. We walk your work, score the candidates, pick the use cases with the cleanest ROI, and kill the ones that look exciting in a demo but do not survive contact with your data.
- Build it right
Ship the thing, not the prototype.
Senior engineers, not a discovery deck. We build against the workflows your team actually runs, integrate with the systems already in place, and put human-in-the-loop on every critical path. No proof-of-concept that quietly dies in a sandbox.
- Deploy in production
Live with budgets, logs, and a retreat path.
Cost ceilings, audit trails, a written policy for what the agent is allowed to do without a human approval. Observability from day one. A defined exit ramp the day it stops paying for itself, so the buyer is never trapped.
- Adopt + enable
Make sure the team actually uses it.
The reason most AI deployments fail is not the model. It is the adoption. We train the operators, document the workflows, sit with the team for the first few weeks of live use, and hand back a runbook the next admin can actually read.
If AI is not the right answer, we say so. We sell the work, not the buzzword.
Which one is yours?
Pick the one that sounds like your week. The answer tells us where to start.
You don't know what to do.
The roadmap has been rewritten three times. Half the team wants a new platform. The other half wants to fix what's there. Nobody has put a number against either path.
We map the work, name the bottleneck, and tell you which fix is worth doing. AI strategy lands in the same deliverable: a roadmap your CFO will sign.
See the diagnostic work BuyBuy the platform. Get it running fast.
monday.com, Odoo, Make.com, or Cerri configured around your operating model. Without the eighteen-month timeline, the seven-figure invoice, or the integrations that break quietly after launch.
We sell the license and we deploy the platform. Senior operators only. AI features turned on where they earn their keep, off where they do not.
See the platform work BridgeYour tools don't talk to each other.
Great products in your stack. They live in their own silos. Data lives in three places, reports get built in spreadsheets, the handoffs between tools happen in someone's head. The integration layer that should exist doesn't.
We build the bridges. Senior-led, production-grade output, not slop. With LLMs in the loop where they help: classification, summarization, intelligent routing.
See the bridge work BuildNothing off the shelf fits.
The workflow is too specific, the data model is yours, or the seventh SaaS subscription would cost more than building the thing. You need an honest read on whether to build, and a team that can do it without a dependency you regret.
We build the narrow piece, integrate it, and hand it back maintainable. AI-multiplied, senior engineers leading. Vibe coding in service of production, not demos.
See the build workBuilt for shipping. Measured on outcomes.
We don't bill discovery. We don't bill "phase one of seven." We bill on what's running in production. These are the numbers across the engagements we're running right now.
The thinking behind the build.
Where most engagements start. Each one maps to a deliverable your CFO can sign and your COO can act on. Not a slide library of "potential use cases."
- A.01 AI Strategy An AI roadmap your CFO will sign and your COO can actually execute. Sequenced, scoped, and tied to specific workflows. Not a library of "potential use cases."
- A.02 AI ROI & Benefit Analysis Quantify the benefit before the contract. Re-quantify after delivery. Built around the numbers you defend to the board, not the ones the vendor gave you.
- A.03 Value Stream Mapping Find the real bottleneck before you spend on AI or software. We walk the work, not the org chart, and produce the constraint map that tells us where AI multiplies and where it does not.
How we work.
Four principles, applied across every engagement. They're the reason we ship in 30 days instead of 6 months.
-
Walk the work first.
We don't write the SOW from the call. We map the actual flow (what triggers what, where data lives, who owns each handoff) and only then do we propose. The proposal is half the work.
-
Ship in increments your team can absorb.
The fastest project is the one that doesn't get re-trained, re-deployed, or re-bought when it lands wrong. We ship to production weekly, with rollback paths your ops team owns.
-
Own the outcome, not the SOW.
We measure the engagement against the operating metric you actually report on: cycle time, first-pass yield, OPEX recovered. Not delivered hours.
-
AI is a multiplier, not the strategy.
We do not start with "what could AI do?" We start with "what is broken in your operations?" Then we apply AI where it multiplies, not where it impresses. The AI strategy that ships is the one tied to a specific workflow with a measurable outcome. Not the one with the best slide.
Four platforms.
AI multiplied across all of them.
Each practice is staffed by senior operators who've deployed the platform in production AND brought AI into it. Not junior consultants reading a deployment guide for the first time. Not generic AI consultants who do not know the platform.
Work Management, AI-enabled
Stand up monday.com so it actually runs the business. Workflows, automations, integrations, and AI features (monday AI, custom GPT integrations, automated classification) that produce visible operating lift. Plus the governance to keep it from sprawling into chaos in twelve months.
Explore the practiceBusiness Systems, AI-multiplied
Implement Odoo across finance, operations, sales, and inventory with AI-powered automation in every module. Without the eighteen-month timeline or the seven-figure SI invoice from the big firms. AI invoice processing, intelligent reconciliation, automated reporting from day one.
Explore the practiceAutomation, with AI routing
Wire your stack together with LLMs in the loop. Intelligent classification, AI-driven decisioning, and dynamic routing that the simple if-then automations of three years ago can't touch. Auditable, observable, and not held together with duct tape and goodwill.
Explore the practiceProject Operations, AI-augmented
Bring portfolio visibility to PMOs running fifty-plus concurrent projects. AI-powered status summarization, automated risk flagging, and predictive timelines layered on top of Cerri's structured project data. Rolled out the way Cerri was actually designed to be used, with reporting your CFO trusts.
Explore the practiceBuilt to fail safely.
AntlerWing is embedded in client systems. We touch real data and ship real automations. How we do that responsibly (data handling, AI safety, sub-processors, incident response) is documented on one page, not buried in a deck.
Bring us
the messy one.
The system that's been on the roadmap for two years. The migration that's already failed once. The AI strategy that didn't make it past the deck. That's the one we want.