Your operations team is managing tasks that should manage themselves
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
RaftLabs builds business operations automation covering SLA monitoring and escalation, task assignment and routing, approval workflows, cross-system data sync, recurring task scheduling, exception management, and operational KPI tracking. We scope every project at a fixed cost and ship in 10–14 weeks. Projects focused on a single workflow, like SLA monitoring or approval routing, typically deliver in 4–6 weeks.
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Operations automation isn't about replacing judgment — it's about removing noise
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.
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.
Capabilities
What we build
SLA monitoring and escalation
Cases, tickets, and tasks that breach SLA commitments are almost always visible in advance -- they just aren't being watched systematically because the operations team relies on individuals to notice and escalate rather than on a system that watches every item continuously. SLA monitoring built here tracks every open item against its configured deadline, calculates the time elapsed and time remaining as a percentage of the SLA window, and fires proactive alerts at configurable thresholds: a warning alert at 70% of the SLA window consumed (while there is still enough time to recover); an escalation alert at 90%; and an automatic escalation to the manager queue if the SLA window reaches 100% without closure. Alert content is specific: the alert includes the case or ticket ID, the customer or subject name, the SLA type and deadline, the current assignee, the time elapsed, and the time remaining -- everything the recipient needs to act immediately without investigating context. Escalation chain configuration: different case types have different escalation paths (a P1 production incident escalates to the on-call engineer and the engineering manager after 15 minutes; a billing query escalates to the senior billing team member after 2 hours); escalation paths are configured per case type, priority, and customer tier without a code change. Integration approach: for teams running on existing ticketing platforms (Zendesk via the Zendesk API, Freshdesk, ServiceNow, Jira Service Management, Linear), the monitoring layer reads ticket state via API and applies escalation logic externally without requiring changes to the ticketing platform configuration. For custom operational systems, the monitoring layer connects to the database or API that tracks case state. SLA performance reporting: breach rate by case type, average time to resolution, and percentage of cases escalated, broken out by team and time period -- the metrics that drive the continuous improvement conversation about which case types need process changes rather than more monitoring.
Task assignment and routing
Manually triaging incoming work -- deciding who gets what, based on type, priority, territory, skill, or workload -- is a daily overhead for team leads that consumes decision-making capacity better spent on the work itself. Routing logic implemented as a configurable rule engine rather than hard-coded decision trees so the operations team can modify routing rules without requesting a code change: rules defined as condition-action pairs ("if work type is 'enterprise support' AND customer tier is 'Platinum' THEN assign to senior support queue AND set priority high AND notify account manager"). Rule evaluation order configurable with fallback rules: if no specific rule matches, the item routes to the default queue rather than sitting unassigned. Routing criteria available: work type (derived from category selection, keyword analysis, or source system), customer tier (read from the CRM account record), geographic region (derived from customer address or time zone), team member workload (current open item count per team member, with assignment throttled when an individual exceeds a configured capacity threshold), skill match (routing to team members with the relevant certified skill or product knowledge for the specific issue type), and time of day (routing to on-call team outside business hours vs. the primary team during business hours). Real-time queue management view: team leads see all queues, current depths, average wait time per queue, and team member workload distribution -- the view that allows capacity rebalancing with a reassignment action rather than waiting for the queue to self-clear. Exception queue for items the routing rules could not classify: unmatched items land in a review queue for a team lead to manually classify and assign, and each manual assignment becomes a potential new rule ("when similar items come in, route them to this queue") that the team lead can configure directly.
Approval workflows
Approval processes that travel by email have two problems: they are slow because each approver waits to discover the request is in their inbox, and they leave no reliable audit trail because email threads are not structured records. A purchase request that needs three sequential approvers can sit for three days in email, with each approver unaware that their step is blocking the next one, and the requester has no visibility into where the request is stuck. Structured approval workflow automation replaces the email chain with a system-managed sequence: the requester submits the approval request through a form or triggered by a system event (a deal reaching a value threshold, a budget line exceeding its amount); the first approver in the chain receives a structured notification (email, Slack, or in-app) with the request details, context, and the relevant policy information needed to make the decision; approving or rejecting takes a single action (click or button) that immediately triggers the next step. Approval routing logic configurable without code: value-based routing (purchase requests under £5,000 require one approval; between £5,000-£25,000 require two; above £25,000 require Finance Director and CEO approval); type-based routing (contract amendments require Legal review; vendor onboarding requires Procurement and Finance); exception routing (any request outside the standard parameters routes to an exception review queue before the normal approver chain). Rejection handling: when an approver rejects a request, they select a reason code and optionally add notes; the requester receives the rejection with the reason and context, and can modify and resubmit directly from the notification without recreating the request. Full audit trail stored per request: who submitted, who approved or rejected at each step, with what decision and what notes, at what time -- the record required for regulatory audits, financial controls reviews, and contract disputes. Reminder escalation: if an approver has not acted within a configured window (24 hours for standard requests, 4 hours for urgent), an automated reminder is sent; if no action after a second reminder, the request escalates to the approver's manager with the delay noted.
Cross-system data sync
When your CRM, project management tool, ticketing system, billing platform, and ERP don't share data automatically, someone acts as the bridge -- copying records, updating statuses, and manually keeping systems aligned. That overhead grows linearly with transaction volume: 50 deals per month means 50 manual project creations, 50 billing record updates, and 50 CRM status synchronisations. At 200 deals, that is half an FTE doing data entry. The sync automation maps the specific interactions between your systems, defines the trigger events (deal status changed to Won in HubSpot), the corresponding data operations (create project in Asana with the deal name, value, client name, and kickoff date; create billing record in Xero with the contracted value and payment schedule), and builds the integration layer using each system's API. Systems connected in typical operations automation engagements: CRM (Salesforce REST/Bulk API, HubSpot v3 API) to project management (Asana REST API, Monday.com API, Jira REST API); project management to billing (Xero API, QuickBooks Online API, FreshBooks API); ticketing (Zendesk API, Freshdesk API) to CRM; and inventory/ERP (NetSuite SuiteTalk, SAP RFC) to CRM and billing. Conflict resolution when both systems have modified the same record: configurable per field -- last-write-wins for simple status fields; source-of-record-wins for fields where one system is authoritative (the CRM is the authoritative source for customer name; the ERP is authoritative for pricing). Sync monitoring with per-integration health dashboards so sync failures surface to the operations team before they cause downstream data quality problems, not when an analyst notices a discrepancy in a report three weeks later.
Recurring task scheduling
Compliance checks, weekly reports, daily reconciliations, monthly account audits, quarterly licence renewals -- recurring operational tasks that run on a fixed schedule but still require someone to kick them off manually add a predictable but unnecessary administrative overhead to every week. Scheduled task automation handles: daily automated reconciliation runs that compare records across two systems, flag discrepancies above a configurable tolerance, and generate an exception report for the team rather than requiring someone to manually pull exports and run the comparison; weekly KPI report generation that pulls data from all connected systems, calculates the configured metrics, formats the report, and delivers it to distribution list recipients -- so the weekly management pack compiles itself overnight and appears in inboxes before the Monday stand-up rather than consuming two hours of a data analyst's Monday morning; monthly compliance certificate or licence expiry checks that scan the compliance record database, identify items expiring within a 90-day window, and notify the responsible owner with the specific item, expiry date, and renewal action required -- the process that catches a professional indemnity insurance expiry before it becomes a contract compliance problem rather than after; and automated backups, data archival jobs, and database maintenance tasks that run at scheduled intervals without requiring an engineer to trigger them. Scheduler built on a reliable job queue: AWS SQS + Lambda for serverless scheduling; or a managed scheduler (AWS EventBridge Scheduler, cron jobs on ECS) depending on the frequency and latency requirements of each task. Failed job retry with exponential backoff and dead letter queue alerting so a failed task does not silently drop -- the operations team receives an alert for any task that fails after the configured retry attempts, with the failure reason and the last successful execution date.
Operational KPI tracking and dashboards
Operational dashboards that require a team member to pull data from five systems, paste it into a spreadsheet, and apply formulas every Monday morning are not dashboards -- they are weekly manual reports that happen to contain charts. Real-time KPI dashboards built here pull from all connected operational systems via API or scheduled database query, calculate the configured metrics on the incoming data, and display current values without any manual refresh step. Metrics tracked per operations team type: for support operations, SLA attainment rate (percentage of tickets resolved within SLA by priority tier), first response time (average time from ticket creation to first agent response), ticket volume by category and channel, open queue depth by team, and escalation rate (percentage of tickets escalated to Tier 2 or management); for process operations, task completion rate vs target, average task cycle time, approval workflow cycle time by type, exception rate (tasks requiring manual intervention outside the standard process), and cross-system sync error rate. Dashboard built in the BI tool already in use (Metabase, Looker, Tableau, Power BI) by connecting to a centralised operational metrics database populated by the sync and automation layer. Alternatively, built as a standalone dashboard application (React with Recharts or D3.js) if a separate tool is not in use or if the dashboard needs to be embedded in an existing operations portal. Alert layer on top of the dashboard: when a metric crosses a configured threshold (SLA attainment rate drops below 90%, queue depth exceeds 150 items, escalation rate spikes above 15% in the last 4 hours), an alert fires to the relevant team lead via Slack and email with the specific metric, current value, threshold, and a direct link to the dashboard view showing the breakdown. The dashboard is always current; the alerts make it active rather than passive.
What's your ops team handling manually that should run itself?
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.
The 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 — purchase approvals, contract sign-offs, exception authorizations — that currently travel by email 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.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Business Operations Automation in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
