Hi, I'm Ari 👋
I can help you automate tasks and answer questions about your business.
Services > Custom Automation Engineering
CUSTOM AUTOMATION ENGINEERING
Custom internal tools that automate the operations no-code platforms cannot handle. Rules engines, dispatch systems, approval workflows, scheduling services, orchestration backbones. Built with engineering rigor, owned by you, designed for the operational logic your business actually runs on.
Representative workflow execution. Real engines are designed around your specific operations.
Built in TypeScript, Python, Go. Deployed on AWS, GCP, Azure, or your own infrastructure.
WHERE THIS SERVICE FITS
Custom Automation Engineering is the middle of our service catalog. Below shows how it compares to the alternatives so you can self-qualify which service actually fits your situation.
Configuration on a no-code platform.
Build workflows by configuring an existing platform. Fastest path to working automation when the platform fits the use case.
PICK THIS IF
Or read about Zapier Consulting
Custom code connecting systems.
Code that connects two or more systems via APIs, webhooks, or events. Focused on the connection layer, often without significant business logic.
PICK THIS IF
Or read about API and System Integrations
Custom code that runs operational workflows.
Custom internal tools and engines. Workflow orchestration, rules engines, dispatch systems, approval flows. Code with real business logic, not just plumbing.
PICK THIS IF
A complete platform built around your business.
Multi-module software systems. Sales platform (CRM), operations platform (ERP), or other domain-complete builds. The biggest, most expensive service we offer.
PICK THIS IF
Or read about Custom CRM Development
WHAT WE BUILD
Each one represents a category of internal tool we have shipped multiple times. Different shapes of software, but all sharing the same core: custom-coded business logic that automates an operational workflow.
Workflow orchestration engines
MULTI-STEP BUSINESS PROCESSES
Engines that execute multi-step business processes with branching logic, retries, timeouts, and state. Often replace the long sequential workflows that get unwieldy on no-code platforms.
TYPICAL FOR
Customer onboarding, claim processing, multi-stage approvals, customer lifecycle automation.
Dispatch and routing systems
DECIDING WHO HANDLES WHAT
Custom logic that decides which person, team, or resource should handle a given task. Considers availability, skills, territory, priority, and your specific business rules.
TYPICAL FOR
Field service dispatch, lead routing, customer support triage, case assignment.
Rules engines
BUSINESS LOGIC AS CODE
Custom engines that evaluate business rules and return decisions. Pricing, eligibility, scoring, fraud detection. Centralizes logic that would otherwise live in spreadsheets and individual heads.
TYPICAL FOR
Pricing engines, quote generation, eligibility checks, lead scoring, risk scoring.
Approval workflow systems
STRUCTURED DECISION MAKING
Custom approval chains with branching, escalation, parallel approvals, and audit trails. More structured than email approvals, more flexible than what off-the-shelf tools offer.
TYPICAL FOR
Expense approvals, contract reviews, hiring approvals, finance authorizations.
Scheduling and capacity systems
RESOURCES AND TIME
Custom systems that allocate finite resources across competing demands. Schedules, rooms, equipment, technicians, instructors. Complex constraint logic that off-the-shelf scheduling tools cannot model.
TYPICAL FOR
Multi-location service scheduling, equipment scheduling, training programs, surgery scheduling.
Alert and notification orchestration
WHO GETS TOLD, WHEN, AND HOW
Custom logic for what triggers alerts, who receives them, through which channel, with what escalation. Replaces a tangled mess of disconnected notification rules across multiple tools.
TYPICAL FOR
Operational alerts, customer notifications, internal status updates, escalation chains.
ARCHITECTURE APPROACHES
Every custom automation project picks one or two of these patterns. Choosing the right pattern is half the architecture work. The other half is implementing it without skipping the operational reliability pieces.
An engine that runs business processes as a series of steps with built-in retry, timeout, and resumption logic. Often implemented on top of Temporal, custom Postgres-backed engines, or open-source workflow runners.
WHEN WE PICK IT
Multi-step business processes where each step might fail, retry, or wait. Customer onboarding, claim processing, fulfillment flows.
The business entity (a contract, a deal, an order) moves through defined states with rules governing transitions. Implemented with XState or hand-coded state machines. State is the source of truth.
WHEN WE PICK IT
Workflows where the entity's current state matters more than the steps that got it there. Approval flows, lifecycle management, status-driven processes.
Events get published to a bus and multiple downstream services react independently. Decouples producers from consumers. Implemented with Kafka, AWS EventBridge, Pub/Sub, or simpler pub-sub patterns.
WHEN WE PICK IT
When one upstream event needs to trigger many downstream actions reliably, or when you need to add new reactions without changing the source.
Workflows that run on a schedule. Daily reports, weekly billing, monthly closes, periodic syncs. Implemented with cron, scheduled Lambda, or workflow-engine schedules.
WHEN WE PICK IT
Operational tasks that happen on a fixed cadence regardless of upstream events. Reporting, batch processing, periodic maintenance.
Work gets enqueued and processed asynchronously by a pool of workers. Built with BullMQ, AWS SQS, RabbitMQ, or similar. Handles high-volume async work with retry and dead-letter queue patterns.
WHEN WE PICK IT
High-volume async work where each item is independent. Email sending, data processing, webhook handling, batch operations.
REAL PROJECTS
Anonymized for client confidentiality. The architecture and operational impact are real.
A regional HVAC company with 80 technicians across three states was dispatching using a spreadsheet plus phone calls. Drive time was killing margin. Customers complained about unpredictable arrival windows. The off-the-shelf field service platforms had been evaluated and dismissed for being too rigid around their specific service offerings.
ENGINE PATTERN
Dispatch and routing with rules-based decisioning
WHAT WE BUILT
CORE LOGIC
Skill-matching, drive-time optimization, customer priority tiers, technician capacity rules, real-time re-routing on no-shows.
INTEGRATIONS
IMPACT
Drive time cut 31%
Translated to capacity for 14% more service calls per day without adding technicians.
A B2B SaaS company with complex enterprise pricing was running quotes through a spreadsheet that only three people understood. Quote turnaround was three to five business days. Errors were common. Deal velocity was suffering.
ENGINE PATTERN
Rules engine with versioning and audit trail
WHAT WE BUILT
CORE LOGIC
Volume-tiered pricing, custom contract terms, geographic adjustments, approval thresholds, automatic discount eligibility.
INTEGRATIONS
IMPACT
Quote turnaround dropped to under 1 hour
Sales reps generate quotes themselves. Finance only touches edge cases. Win rate improved 12% from faster response.
A 200-person company was running expense approvals, vendor approvals, and contract approvals through email chains. Compliance was concerned about audit trail gaps. Approvers were frustrated by lost context. CFO wanted to see real-time status of every approval in flight.
ENGINE PATTERN
State machine driven with parallel approval chains
WHAT WE BUILT
CORE LOGIC
Routing based on amount and category, parallel approval where required, escalation on inactivity, complete audit trail per record.
INTEGRATIONS
IMPACT
Approval cycle time down 64%
From an average 4.2 days to 1.5 days. Audit trail accepted on first review by their compliance team.
A dental practice group was running scheduling at each location independently. Patients calling the group line could not be routed to the right location easily. Hygienist utilization varied wildly. The off-the-shelf practice management software handled per-location scheduling but not cross-location optimization.
ENGINE PATTERN
Constraint-based scheduling with queue processing
WHAT WE BUILT
CORE LOGIC
Per-location capacity, hygienist specialization, patient location preference, insurance acceptance per provider, recall cadence.
INTEGRATIONS
IMPACT
Hygienist utilization up 18%
Across all 40 locations. Patient no-show rate also dropped 22% from better reminder orchestration.
OPERATIONAL RELIABILITY
Automation engines fail differently than typical web services. They run for minutes, hours, or days. They maintain state between steps. They are harder to debug when something goes wrong. The five concerns below are what we engineer for from day one.
Workflow engines often run for hours or days. A server restart in the middle should not lose the workflow's state. Persistent state is non-negotiable for any automation that matters.
OUR APPROACH
All workflow state persists to durable storage (Postgres or equivalent) at every step boundary. A workflow can resume from any step after any kind of restart. Tested by intentionally restarting services mid-workflow during development.
When a workflow runs for three hours, you need to see what it is doing right now, what step it is on, what data it is operating against. Black-box workflows are unmaintainable.
OUR APPROACH
Every step logs structured events. Every workflow has a live status view showing current step, recent history, and elapsed time per step. Dashboards are part of the deliverable, not an afterthought.
When step 7 of a 10-step workflow fails, you do not want to re-run steps 1 through 6. The engine should resume from where it failed, after the underlying problem is fixed.
OUR APPROACH
Engines support resumption from any step. Failed workflows go to a queue for human review. After fixing the underlying issue, workflows resume from the failure point, not the beginning. Idempotency keys prevent duplicate work on retry.
When the engine processes faster than downstream systems can accept, retries and rate limits cascade into outages. Volume should pace itself against actual downstream capacity.
OUR APPROACH
Token bucket pacing per downstream service. Backpressure signals from queues throttle producers. Adaptive concurrency that responds to error rate in real-time. Built into the engine, not bolted on later.
For regulated industries and any business that takes operational rigor seriously, you need to be able to answer 'what happened, when, and why' for any workflow run, sometimes years later.
OUR APPROACH
Append-only audit log of every step decision, input, output, and timing. Audit log lives in your infrastructure with retention policies you set. Standard reports for SOX, SOC 2, and HIPAA audits built in where applicable.
HOW WE BUILD
Automation engineering projects are smaller than CRM or ERP builds. Most ship in two to three months. The phases are leaner because the scope is more focused.
Understand the workflow, pick the engine pattern, sketch the architecture. The pattern choice (orchestration, state machine, event-driven) is locked in this phase.
DELIVERABLE
Architecture document, engine pattern decision, integration map.
Develop the core engine, business logic, integrations, and admin UI if needed. Bi-weekly demos to your team. State persistence and observability built in from the first sprint.
DELIVERABLE
Working engine in your staging environment with test data flowing.
Run real workloads through the engine in production with monitoring. Validate accuracy, performance, and reliability against the operational metrics that matter.
DELIVERABLE
Engine running production traffic with validated success metrics.
Operations runbook, architecture documentation, training for your team. Optional retainer for ongoing development. Most clients stay on retainer for the first quarter post-launch.
DELIVERABLE
Documentation, runbooks, trained internal owner, optional ongoing engagement.
Total build time runs 6 to 14 weeks depending on engine complexity and integration scope. We firm up the timeline after Phase 1.
WHERE WE BUILD THIS MOST
Custom automation engineering shows up most often in these six operational areas. The patterns repeat across industries: the dispatch system for HVAC looks structurally similar to the dispatch system for couriers.
Dispatching, routing, and scheduling for businesses with workers in the field. Reduces drive time, increases jobs per day, improves customer experience.
EXAMPLES
Quote generation, pricing rules, deal approvals, commission calculations. Custom logic that lives at the heart of how your business sells.
EXAMPLES
Expense approvals, vendor onboarding, payment workflows, intercompany transactions. Audit-grade approval logic with full traceability.
EXAMPLES
Onboarding orchestration, lifecycle automation, churn prevention triggers, success milestone tracking. The workflows that run customer-facing operations.
EXAMPLES
Hiring workflows, onboarding orchestration, IT provisioning, access management. The internal operations workflows that bigger companies hand-off through tickets.
EXAMPLES
Custom data pipelines with business logic, automated reporting, anomaly detection, recurring data workflows. More than ETL because there is real business logic involved.
EXAMPLES
FAQ
What buyers ask before committing to custom automation engineering work. Click to expand any answer.
WHEN YOU NEED REAL ENGINEERING
Forty-five minutes. Walk us through the operational workflow you want automated, the systems involved, and what your team has already tried. We will tell you whether this service is the right fit, what an engine looks like, and what it would cost to build and run.
Book an engineering scoping callNo pressure. Just value.
Hi, I'm Ari 👋
I can help you automate tasks and answer questions about your business.