AI OCR for gas station operations
- 20K+
- transactions in a single day during real-world testing
Business Operations Automation Software
Most operations problems aren't resource problems, they're process problems. SLAs breach because nobody noticed the escalation window closing. Tasks sit unassigned because routing decisions are made manually. Reports take hours to compile because data lives in three systems that don't sync. We build operations automation that handles SLA monitoring, task routing, approval workflows, and cross-system data sync so your team runs on exceptions, not on manual coordination.
SLA breach risk flagged automatically before the window closes, not after
Incoming work routed to the right person or queue based on configurable rules, not manual triage
Approval workflows that move without email chains or chasing
Cross-system data kept in sync automatically so reports reflect what's actually happening
Recent outcomes
Operations automation · Gas station chain
20K+ transactions in a day
Built an AI OCR pipeline that processed 20,000+ transactions in a single day during real-world testing, replacing a spreadsheet-based reconciliation process.
Process automation · B2B SaaS platform
0% order errors
Automated multi-platform order management for Gula, eliminating order errors entirely, MVP launched in 16 weeks.
The problem
How many SLA breaches last month could have been caught 30 minutes earlier with an automated alert?
Are your managers spending time chasing status updates instead of managing outcomes?
Short answer
RaftLabs builds business operations automation for teams across the US, UK, Europe, Canada, and the UAE: SLA monitoring, task routing, approval workflows, and cross-system data sync. A first workflow ships as a fixed-price v1 in 4-6 weeks; broader multi-workflow platforms grow over 10-14 weeks.
Key takeaways
Trusted by


Proof
The best operations teams aren't the ones with the most people. They're the ones who've figured out which work requires human judgment and which doesn't. Escalation decisions, resource allocation, exception handling, those need people. SLA alerts, task routing, data sync, and recurring report generation don't.
Two numbers frame the shift. McKinsey found 72% of organizations were using AI in at least one business function in early 2024, up from 55% a year earlier (McKinsey, The State of AI in early 2024). And Gartner projected that organizations combining automation with redesigned operational processes would cut operational costs by 30% (Gartner, 2021). The teams moving fastest are not adding headcount. They are drawing a clear line between work that requires judgment and work that follows a rule, then automating the second category.
When your team is spending time on the second category, they have less capacity for the first. That's the operations problem. We fix it by automating what should be automatic.
The case for automating
Capabilities
Cases, tickets, and tasks that breach SLA commitments are almost always visible in advance; they just aren't watched systematically. SLA monitoring tracks every open item against its deadline and fires alerts at configurable thresholds, with escalation paths configured per case type, priority, and customer tier without a code change.
Manually triaging incoming work is a daily overhead for team leads that consumes decision-making capacity better spent on the work itself. Routing runs as a configurable rule engine, so operations can change rules without a code request, routing by work type, customer tier, region, workload, skill match, or time of day. Unmatched items land in an exception queue where each manual assignment can become a new rule.
Approval processes that travel by email are slow and leave no reliable audit trail. Structured approval workflows replace the email chain: requests are submitted by form or system event, each approver gets a notification with full context, and one click approves or rejects and triggers the next step. Every request keeps a full audit trail for regulatory and financial reviews, and reminder escalation nudges slow approvers, then escalates to their manager.
When your CRM, project management, ticketing, billing, and ERP systems don't share data, someone acts as the bridge, and that overhead grows with volume. Sync automation maps trigger events to data operations using each system's API, conflict resolution is configurable per field, and per-integration health dashboards surface sync failures before they cause downstream data problems.
Recurring operational tasks that run on a fixed schedule but still need someone to kick them off add unnecessary overhead to every week. Scheduled automation handles daily reconciliations, weekly KPI reports that land before the Monday stand-up, and monthly compliance checks that catch licence and insurance expiries 90 days out. It runs on reliable job queues with retries, dead letter queues, and failure alerts so nothing drops silently.
Operational dashboards that need a team member to pull data from five systems every Monday are weekly manual reports that happen to contain charts. Real-time KPI dashboards pull from all connected systems via API, calculate the configured metrics, and stay current without a manual refresh step. An alert layer makes it active: when SLA attainment drops or queue depth spikes past a threshold, the team lead gets an alert with a direct link.
The point of operations automation is not a dashboard. It is moving the same work off your team's plate without losing the audit trail or the exception handling. Here is the before and after, workflow by workflow.
| Manual coordination | Operations automation | |
|---|---|---|
| SLA breaches | Noticed after the window closes, usually in the customer complaint | Flagged at a configurable threshold, with lead time to act |
| Incoming work | Triaged by a team lead, one item at a time | Routed by rule on type, tier, region, and workload; misfits go to an exception queue |
| Approvals | Chased over email, no reliable audit trail | One click, full context, complete audit trail for every request |
| Cross-system state | A person re-keys data between CRM, billing, and project tools | Trigger events sync the systems, conflicts resolved per field |
| Failures | Discovered when a report comes out wrong | Surfaced by per-integration health dashboards and alerts before downstream damage |
How we work
Every project follows the same four phases. Scope is locked and price is fixed before development starts.
We map the specific workflows you want to automate, the systems involved, the rules that govern each process, and the volume of work each workflow handles. You leave week 1 with a written scope document and a fixed-price quote. No development starts without your sign-off.
We design the automation logic, integration points, and exception-handling rules before writing production code. Decisions made here cost a fraction of the same decisions made mid-build. The spec is locked before development starts.
Working automation in a staging environment by the end of sprint one. Bi-weekly demos. QA runs in parallel with every sprint, not as a separate phase at the end. Integration tests run against real data before any workflow touches production.
Production deployment with monitoring active on launch day. Alerts configured for failed jobs, sync errors, and threshold breaches. 8 weeks of post-launch support included in every project.
Automation fails in predictable ways. We design against each one from week 1, and we say so up front because pretending these risks do not exist is how projects go sideways.
Why us
The engineers who assess your automation problem also build the solution. No bait-and-switch, no offshore handoff after the contract is signed. The team you meet in week 1 ships in week 12.
We scope the work, calculate the cost, and lock it in writing before any development starts. A scope change is a change request: priced, agreed, or dropped. It never absorbs into the project and appears on the final invoice.
Clients include Vodafone, T-Mobile, Aldi, Nike, Cisco, and Lockheed Martin. Track record across AI, SaaS, mobile, automation, and enterprise platforms across healthcare, fintech, logistics, and hospitality.
GDPR, HIPAA, SOC 2 compliance requirements are scoped in week 1, not retrofitted before launch. We have shipped HIPAA-compliant systems for US healthcare clients and GDPR-compliant products for European markets.
Every automation project starts with a baseline: current manual hours per process, error rate, and cost per transaction. We size the automation against that baseline so you know the expected ROI before a line of code is written.
We scope operations automation at a fixed cost. Tell us the process and we'll tell you what's automatable and what it'll take.
What clients say
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!
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Read moreThe best candidates share three characteristics: they're high-frequency, they follow defined rules, and they currently require a human to coordinate rather than decide. SLA monitoring fits perfectly, checking whether a case, ticket, or task is approaching its deadline and escalating it is a rule-based action that a system handles better than any individual manager who has 80 other things to watch. Task routing is another strong candidate: deciding which team member or queue receives an incoming request based on type, priority, territory, or workload is a rules problem, not a judgment problem. Approval workflows that currently travel by email (purchase approvals, contract sign-offs, exception authorizations) are a major source of delay and missed steps that automation eliminates. Recurring task scheduling (weekly compliance checks, monthly report generation, daily reconciliation runs) and cross-system data synchronization (ensuring your CRM, project tool, and billing system reflect the same state) round out the most common automation targets.
SLA monitoring automation works by watching the timestamps on your cases, tickets, or tasks and comparing them against the SLA rules defined for each type. When a case approaches 70% or 80% of its allowed resolution time without being closed, the automation fires an alert to the assigned handler with the case details and remaining time. If no action is taken within a defined window, the escalation triggers automatically, a notification to the handler's manager, a status change in the system, or both. The escalation chain, thresholds, and alert content are all configurable and defined during the scoping phase. Your managers stop hearing about SLA breaches after they happen and start seeing at-risk cases with enough lead time to prevent them. For operations running on ticketing platforms like Zendesk, Freshdesk, or ServiceNow, the automation integrates directly. For custom systems, we build the monitoring layer on top of your existing data.
Most operations teams run on multiple tools that don't share data automatically, a CRM, a project management tool, a ticketing system, a billing platform, and sometimes a collection of spreadsheets that bridge the gaps. When a deal closes in the CRM, someone has to manually create the project in the project tool. When a project is completed, someone has to update the billing system. When billing records change, someone has to update the client record in the CRM. Every manual step is a lag, an error risk, and an ops overhead. Cross-system sync automation defines trigger events in each system and the corresponding data updates in connected systems. When a deal closes, the project is created automatically with the right details. When a project milestone is hit, the relevant billing record updates. The sync is bidirectional where needed and configurable in terms of what data flows where and when. Your team stops being the API between your tools.
We start with a scoping conversation, 60 to 90 minutes, where we map the specific processes you want to automate, the systems involved, the volume of work each process handles, and the current manual overhead. From that, we produce a proposal with a defined scope, a fixed price, and a delivery timeline. Nothing gets built on a time-and-materials basis where the final cost is uncertain. Focused automation projects, a single workflow like SLA monitoring with escalation, or approval routing for one department, typically take 4 to 6 weeks and cost correspondingly less. Broader projects covering multiple workflows, several system integrations, and a reporting layer are typically 10 to 14 weeks. The proposal breaks the scope into phases so you can see exactly what gets built in what order, and we can start with the highest-value process if you want to validate the approach before extending it.
We integrate with the tools your team already uses rather than replacing them. Common integrations include CRMs (Salesforce, HubSpot), project management platforms (Asana, Jira, Monday.com), ticketing systems (Zendesk, Freshdesk, ServiceNow), billing and accounting tools (Xero, QuickBooks Online), and ERP systems (NetSuite, SAP). For teams running on custom internal systems, we connect via REST API or direct database access. The integration layer is documented and testable so your team understands what is connected and how.
Yes, we sign an NDA before any scoping conversation involving proprietary process data or system architecture. For US clients, contracts are governed under US law; for UK clients, under English law. Data accessed during the build lives only in the agreed development environments and is not retained after project close. For clients with specific data residency requirements (US-only, EU-only), we scope the infrastructure accordingly from week 1.
Work with us
We scope Business Operations Automation in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.