Audit
Read-only access. We map where the work actually happens and where it breaks
Add intelligence to your workflows.
Most AI pilots don't fail on the model. They fail on having no one who's actually done this before.
The failure pattern
Obvious in hindsight, unstaffed in the moment.
A prompt that works on one document fails on the next, because the formats never match — and by the time that's obvious, the team that built the pilot has moved on to the next one. Every major operational shift has looked like this early: obvious in hindsight, unstaffed in the moment.
We deploy production AI agents into finance, recruiting, and logistics operations — and where you don't have the engineers to build it yourselves, we place ours, embedded and supervised, until it runs on its own. Deterministic where the work is deterministic, models only where judgment is genuinely required, accuracy measured rather than assumed.
Method
Reliability is architecture, not prompting.
Point a language model at messy operational data and it will be right most of the time — and wrong often enough that nobody trusts it with real work. The fix isn't a better prompt. It's structure.
Deterministic logic handles everything that can be resolved by rule. Models handle only the genuine ambiguity that's left. Every output is measured against a labeled set, so accuracy is a number you can see rather than a claim you have to take. As the system runs, the ambiguous cases shrink — the corrections your team makes become training data, and the process gets more predictable over time, not less.
The same discipline applies to agents. An agent that chooses its next action freely will eventually choose wrong. One that proposes an action and has it validated before execution will not.
Process
Four steps, each with a timebox.
- 01 1–2 weeks
- 02 1–2 weeks
Architecture
What gets handled by rule, what needs a model, what stays with a person
- 03 4–6 weeks
Deploy
Running in your environment, on your systems, measured against a labeled set
- 04 Ongoing
Operate
We run it until your team is ready to take it. Or keep running it
Work in progress
Artifacts are being prepared for publication.
Finance — AR Agent
A live agent handling accounts receivable reconciliation and exception routing.
Recruiting — Agent System
TBD pending confirmation of which system this refers to and how it may be presented.
Logistics — Agent System
TBD pending confirmation this is a real deployed system with a measured result.
Judgment
The judgment stays with your team.
We don't automate people out of decisions. We automate the work around the decision — the gathering, matching, reconciling, and chasing that consumes the day. What reaches a person is the exception that actually needs them, with the reasoning attached.
Every decision the system makes is recorded and explainable. When your auditor, your board, or your own controller asks why something happened, there's an answer.
Operations
We run it until you don't need us to.
Deployment isn't a handoff. We operate the system in production — monitoring, correcting, tuning — until your team is ready to take it, and stay on for ongoing support if that's what you want. You're never handed a system and a manual.
Ownership
What's yours stays yours.
Your data, your integrations, and anything built specifically for your workflows belong to you. The underlying platform stays ours, which is why deployment takes weeks instead of quarters — we're not rebuilding foundations for every client.
Why Cruitbase
We ran these functions before we automated them.
We've spent our careers inside the finance, recruiting, and operations functions we now automate — not advising from outside, running them. We build and deploy the agents ourselves, and where a client doesn't have the engineers to do it internally, we place ours, embedded and supervised, until the system runs on its own. Proven today in finance, recruiting, and logistics.
FAQ
The questions we actually get.
What happens on the discovery call?
30 minutes. You describe where the work piles up; we tell you whether it's a fit and what the first phase would look like. No deck.
How long until an agent is in production?
Typically six to eight weeks from the end of the audit. Faster when the data is clean, slower when it isn't.
What can agents actually do?
Reconciliation, matching, chasing, exception routing, document extraction, and the reporting around them — proven today in finance, recruiting, and logistics. Where you don't have the engineers to build this yourselves, we can also place the people who do, embedded and supervised, until the system runs on its own.
Will it work with our existing systems?
Yes. Nothing migrates. Agents run against what you already have.
How much of our team's time does this take?
Under 20 hours total across the engagement, mostly in the first two weeks.
How do you handle security?
Read-only access during the audit. Deployment runs in your cloud under your controls. If you have your own agreements with model providers, we use them.
Who owns what we build?
Your data, your integrations, and anything custom to your workflows are yours. The underlying platform stays ours — that's why deployment takes weeks instead of quarters.
How does pricing work?
A fixed fee for the deployment, a component tied to the outcome once it’s running, and a monthly operating fee if you want us to keep running it. Scoped after the first conversation.
Book a call
Tell us where the work piles up.
30 minutes. You describe where the work piles up; we tell you whether it's a fit and what the first phase would look like. No deck.
Book a call