Automation that clears the queue and knows when to ask.
AI workflow automation services for the repetitive work eating your team's week (intake, triage, data entry, reporting), with a human checkpoint wherever judgement matters. Built into the tools you already run, every action logged.
Reply within four business hours (typical) · Humans in the loop
In one answer
PixelCrayons automates repetitive workflows (intake, triage, data entry, reporting) inside the tools you already use. Human-in-the-loop checkpoints sit wherever judgement matters, every action is logged for audit, and each automation is evaluated against your own baseline before it runs unattended. The first working pilot runs on one real queue. Direct for brands, white-label for agencies.
Discovery maps where your team's hours actually go and picks the first workflow on evidence: high volume, clear rules, painful to do by hand. Intake, triage, data entry and reporting usually top the list. If a workflow shouldn't be automated (too much judgement, too little volume), the discovery document says so.
Week zero
02
Human-in-the-loop, by design
Wherever a step involves judgement (approvals above a threshold, exceptions, anything customer-facing that could go wrong expensively), the automation stops and asks. A person approves, edits or rejects, and the system learns the boundary. The goal is your team spending its hours on decisions, not on typing.
Every build
03
Built into your existing tools
No rip-and-replace. Automations wire into the helpdesk, CRM, ERP, spreadsheets and inboxes your team already lives in, so adoption never depends on anyone changing how they work. If a system has no API, we find the seam. That's the craft part of the job.
Included
04
Evaluation & audit logs
Before an automation runs unattended, it runs supervised against real cases from your queue. Its accuracy is then measured against your own baseline, not a vendor benchmark. After launch, every action it takes is logged: what came in, what it did, what it grounded that decision in. When an auditor or an angry customer asks why, you can answer.
Before launch
05
Handover & runbook
Your team gets the runbook and admin training, under IP and ownership terms agreed before work starts: how to adjust thresholds, add a workflow to the queue, read the logs and switch any automation off. A light retainer is the usual shape after launch, for monitoring and the changes the first month teaches. Running it entirely in-house is fine too.
At handover
The pilot
From queue audit to unattended runs.
01
Days 1 to 3
Discovery & queue audit
We watch where the hours go, pick the first workflow on evidence, and agree in writing what correct looks like, including which steps must always stay human.
02
Week 1
Pilot scoped & priced
A written scope lands: one workflow, the systems it touches, the human checkpoints, a demo date. You approve the itemised price before anything is built.
03
Pilot
Working pilot, your queue
The pilot processes real items from your queue, supervised, logged, and measured against the baseline we agreed upfront.
04
Weeks 3 to 6
Evaluate, harden, hand over
Supervised runs become unattended ones only where the numbers earn it. Integrations harden, your team learns the runbook, and we say so plainly if a step should stay manual.
Inside Prism
Your engagement, week to week, in one workspace.
Where the engagement includes it, your AI build runs in a Prism workspace you log into: requests, approvals, the task list and the weekly review, with each decision and its expected result written down.
Any automation looks good on the cases it was built for. What decides whether you can leave it running is what it does with the ones it was not. So we design the exits first and the happy path second.
The run
01
Trigger
A new item arrives (a form, an email, a row, a webhook), and the run starts with a record of what started it.
No decision here
Nothing is decided yet. A trigger that fires twice is de-duplicated on the record, not on a guess.
02
Read and normalise
Fields are extracted and mapped to the shape the downstream system expects.
Field missing or unreadable
The run parks with the item attached and the specific field named. It does not infer a value to keep moving.
03
Classify and route
The item is categorised and sent to the right queue, team or record.
Confidence below the agreed line
Routed to a human with the two candidate categories shown. Every override is captured, which is how the threshold gets tuned with evidence rather than opinion.
04
Act
The write happens (a record created, a status changed, a document filed) inside your system, under a service account you control.
Above the value or risk threshold you set
Held for sign-off before the write, not after. Thresholds are yours to set and change without a developer.
05
Log and reconcile
The action, its inputs, its decision and its actor are written to an audit trail you can query.
Downstream system rejects the write
The run rolls back to the last clean state and raises it. A half-finished run is the one failure mode that quietly corrupts data, so it is designed out rather than monitored for.
When it does not fit
The rule the whole lane is built around: an automation that stops and asks costs you a few minutes. One that guesses costs you the audit.
Illustrative run: a generic approval workflow, not client configuration
How we report it, in Prism
The queue baseline, measured before anything is automated.
What you receive in month one
Automation is reported against the queue it replaces. In the first month you receive the process map with every manual step, its owner and its handoffs, the queue baseline recording volume, wait time and error rate as they stand today, and the exception list naming the cases that will stay with a person. Each workflow ships with its run log and its rollback path.
01Process map: each step, its owner, and the handoffs between them
02Queue baseline: volume, wait time and error rate before automation
03Exception list: the cases that stay manual, and who handles them
04Run log: each execution, its outcome, and the failures retried or escalated
05Rollback path: how the manual process resumes if a workflow is paused
A workflow that needs to reason over your documents connects to a knowledge system. The customer-facing end of the same pipeline is a chatbot. Building on n8n specifically? That has its own page.
Each one says where it applies and links to its full terms.
Response and start times
We typically respond within four business hours. Eligible engagements can typically start within two to three business days after scope, payment and required access are confirmed.
Business hours are Monday to Friday, 9:00 am to 6:00 pm IST, excluding published company holidays. Typical expectations, not guaranteed service levels.
Every delivery is reviewed before release by QA, your Project or Account Manager and a senior delivery lead, and you then review it against the acceptance criteria agreed at the start. Our specialists use AI to support delivery, with people responsible for reviewing the work. Applicable development work includes 30 days of corrective maintenance after production launch.
Who owns the ad accounts, the data and the work?
Your materials, data and accounts remain yours, and we prefer to work in advertising and analytics accounts you own, with access delegated to our team. Agreed ownership rights in bespoke deliverables transfer under the engagement terms and applicable payment; third-party software and assets keep their licences. We do not withhold customer-owned data or accounts over a payment dispute.
What if we want to stop?
Cancellation, notice and any renewal terms are written into your proposal or statement of work before you accept it. If an engagement ends early, we hand over completed, paid-for work and list any unfinished work separately. For an eligible specialist trial, you can stop within the trial window and pay nothing for eligible trial hours.
How will we know what you are doing?
Before work starts we agree how often you get updates, what the reports cover and who sends them. You know who coordinates your engagement, who owns the work and how to escalate an issue. For hourly and retainer work, time is recorded in Workstatus, so you can see the time records behind your invoice.
The ones where volume is high, the rules are clear, and doing it by hand is painful. In most businesses that means intake, triage, data entry and reporting, long before anything glamorous. Discovery maps where your team's hours actually go and ranks candidates on evidence: how often the task runs, how mechanical it is, and what an error costs. The wrong first pick is anything soaked in judgement or politics: automate the boring certainty first, earn trust with the logs, then climb. The discovery document ends with a ranked list and names what shouldn't be automated at all.
No, and any vendor promising to "replace headcount" is writing cheques the technology can't cash. What automation genuinely removes is the repetitive layer: the retyping, routing, chasing and formatting that fills a working week without using anyone's actual skills. What it can't replace is judgement. So we build human checkpoints into every workflow where a decision matters. Teams change shape around that: people stop being the conveyor belt and start being the quality control. We won't attach an invented percentage to it, because your queue isn't an average.
It will, occasionally: the design question is whether errors are visible and recoverable, or silent and compounding. Three mechanisms keep them the first kind. Human-in-the-loop checkpoints sit ahead of any step where an error is expensive. Evaluation before launch runs the automation supervised against real cases from your queue, and it only goes unattended where the measured accuracy earns it; and audit logs of every action (what came in, what it did, what it based that on) mean a mistake can be found, traced and corrected rather than discovered months later. And every automation has an off switch your team controls.
No: that constraint is the brief, not an obstacle. AI-based workflow automation integrates with the helpdesk, CRM, ERP, spreadsheets and inboxes your team already runs. The work meets your stack where it is, rather than holding value hostage to a migration. This matters because most automation projects die on adoption: the moment a workflow requires people to change their habits, usage collapses. Where a legacy system has no API, we find another seam: exports, mail parsing, whatever's reliable. If a platform change ever were genuinely worth it, we'd recommend it separately, with the trade-offs in writing. We never smuggle it in.
Less than a transformation programme, because we don't sell one. Every engagement opens with a scoped pilot (one workflow, your own queue, a working deliverable), so you're pricing a small, defined build. The proposal you receive itemises what ships: the workflow covered, the integrations wired, the checkpoints and logging included, and what handover looks like. Extending to further workflows is priced per workflow, only after the first one has proved itself against your own baseline.
Against your own numbers, taken before we start, never a vendor benchmark or an industry average. In discovery we baseline the queue: how many items arrive, how long they wait, how long each takes, how often errors surface. The pilot is then judged on the same measures, and the evaluation report shows the deltas plainly. That includes any step where the automation is slower or less accurate than the human it assists, which happens and deserves saying. You'll notice this page quotes no "hours saved" headline. That's deliberate: those figures are yours to generate, not ours to invent.
Ask how it picks the first workflow, where humans stay in the loop, and what it measures against. Our answers: discovery ranks candidates on evidence, checkpoints sit ahead of any expensive step, and results are judged against your own baseline. Ask who owns the code at the end. With us, your team does, along with the runbook.
Scope a pilot: one workflow, your own queue, a working deliverable with human checkpoints, audit logs, and results measured against your baseline rather than a brochure.
