Off-the-shelf automation works fine when the workflow is identical every time. It breaks the moment anything varies: a vendor changes an API, a document format shifts, a customer phrases something differently, an upstream system silently adds a new field. We build production-grade automation that handles the variability your current tools can't, with deterministic plumbing, scoped AI for the parts that need interpretation, and the error handling that means it actually keeps running.
Pixelfield is for COOs, ops leads and CTOs at companies where Zapier or Make has hit the wall, manual work fills the gaps and per-task pricing is starting to bite. The seniors who scope the work also write the code. 50+ AI features in production, fastest deployment two months from kickoff to live, and a reputation for telling you when the right answer is fixing the process before automating it.
Hybrid: deterministic plumbing plus scoped AIProduction reliability built inHonest about agent limitsZero surprises, not zero failures
Zapier and Make are excellent at 'if X then Y' on clean APIs. They break the moment anything varies: schema drift, document format changes, judgement calls, multi-step decisions. Per-task pricing scales from $29/mo to $1,800-$3,200/mo during exactly the growth you're trying to capture. Either the workflow gets fragile or the bill gets painful. Often both.
You automated the easy 80% and your team is doing the hard 20% by hand. The 20% is variable, judgement-heavy and growing with the business. Headcount scales linearly with volume; intelligent automation breaks that line. Honest about the savings: 40-70% time reduction on narrow tasks, not full replacement. One reference cut admin from 15 hours per week to 3-4 hours of review.
The most common automation regret is automating chaos: silent duplicates, mis-routed records, downstream cleanup that takes longer than the manual job. Step one is process audit, not 'add an LLM'. We've told prospects to fix their data layer first and walk away from a build. That's the audit doing its job.
Agent demos work because the demo data is clean. Production fails because real inputs vary, APIs change, and silent failures stack for days before anyone notices. The engineering that separates a demo from a production system (retries, idempotency, drift detection, alerting, escalation) is most of the work and almost nobody talks about it.
We sit with your ops team, map the actual process (not the documented one), measure manual time at each step, surface upstream and downstream dependencies and identify what should be deleted, kept manual, or automated. The deliverable stands on its own. You can hand it to another vendor or your team and execute internally if you'd rather.
You receive: process map, automatable-steps shortlist with ROI per step, prerequisites (data fixes, system changes), recommended hybrid architecture, fixed-scope build quote.
We turn the audit into a concrete build plan: which steps run on deterministic rules, which need AI, where HITL checkpoints sit, what the integration surface looks like, what monitoring is required for trust at launch. Cost and timeline are scoped before code is written. We surface integration friction here, not in week six.
You receive: architecture proposal, integration plan, monitoring plan, fixed-phase build quote.
Build runs as a small senior team led by Michal Vavra, with AI and integration engineers embedded with your ops stakeholders. Each release ships behind feature flags with retries, idempotency, schema validation, eval gates on AI components, and shadow runs against real production traffic before any decision is automated.
You receive: a working workflow in staging, then production. Observability and rollback are in place from week one, not bolted on at launch.
At launch we wire in schema-drift alerts, run-success monitoring, exception-queue tracking, cost telemetry per workflow and a feedback loop from human review back into the rules and prompts. You receive runbooks, architecture documentation and a handover session.
Monthly retainer for monitoring, API-change handling, prompt tuning and on-call. Take it in-house whenever you're ready.
Direct answers to the questions COOs and ops leads ask us on every <strong>scoping call</strong>.
Zapier and Make are right for clean, deterministic 'if X then Y' flows on stable APIs at low-to-moderate volume. They break when workflows need interpretation, when schemas drift, when multi-step decisions are needed, or when per-task pricing crosses $500-$3,200/mo. Custom hybrid (deterministic plumbing plus scoped AI) usually wins on cost, reliability and flexibility above that line. We'll tell you which side you're on before quoting a build.
Honestly, not the way the hype suggests. 95% reliability per step compounds to 36% success over 20 steps. Around 11% of teams reach true agent production without heavy babysitting. What works in 2026: scoped agents of 5 to 10 steps with HITL checkpoints, deterministic handoffs between agents, structured outputs, loop detection and budget caps. We build to that pattern. We don't sell autonomous swarms.
We engineer for it from day one: retries with exponential backoff, idempotent writes, schema-drift detection, dead-letter queues, alerting that pages a human, escalation logic for genuine exceptions, and a runbook so on-call knows what to do. Across the industry the killer is silent failure: a reference automation ran 11 days corrupting data before anyone noticed. We design against that. Zero surprises, not zero failures.
Zapier at growth: $500-$3,200+/mo and rising with your task volume. Custom hybrid build: typically £10K+ one-off plus a flat monthly retainer (no per-task tax). For most mid-market ops workflows, the build pays itself back inside six months via headcount-equivalent savings on the manual gap. We quote both numbers in the proposal so the run rate is clear before you commit.
Audit and process map: one week from kickoff. First automated workflow live: six to ten weeks from build kickoff for a well-scoped process. Measurable ROI: typically inside six months for engagements over £30K, via the 40-70% time savings on the automated steps. We size the retainer to that horizon.
You own everything. Workflow definitions, custom code, infrastructure-as-code, prompts, agent logic, monitoring dashboards. No vendor lock-in. After launch you can hand the system to your internal team with a runbook and a training session, or keep us on a monthly retainer for monitoring, API-change handling and tuning. Not a dependency. A choice.
When the underlying process is broken. Automation amplifies chaos, it doesn't fix it. When the volume is too low to justify the build. When the variability is so high that humans-with-tools beats agents-with-rules. When compliance or risk concentrates the decision in a single role that needs to stay human. We'll say so during the audit and point you at the cheaper, more reliable option (often: fix the process first, then revisit).
