Case handling and work allocation for contact centre operators and BPO providers, with Switchboard AI agents on the phone, texts and email.
Screenshots
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See all 77 screens in the product tourEach one is purpose-built for contact centre operations rather than a generic template. They are set out in full below.
Bring calls, emails, texts and web forms into one queue of cases, and allocate each to the right agent based on skill, availability, and customer priority, all from a single workflow engine.
When voice, email, webchat, and social media enquiries are handled in separate queues with different routing logic, customers experience wildly inconsistent wait times and often have to repeat themselves across channels. Supervisors lack a unified view of demand, making real-time staffing adjustments guesswork rather than data-driven decisions.
Channel silos
Each channel operates its own queue, meaning agents sit idle on one channel while another is overwhelmed.
Inconsistent SLAs
Without unified priority logic, high-value customers may wait longer on chat than they would on voice.
Context loss on channel switch
When a customer moves from webchat to phone, agents start from scratch because interaction history is not carried across.
Manual queue rebalancing
Supervisors must manually drag and drop agents between queues during spikes, wasting precious minutes.
Unified case queue
Emails, texts, portal requests and calls logged as cases enter a single prioritised queue before they are allocated.
Skills-based allocation rules
Allocate cases by agent skill, availability, current workload and customer segment.
SLA warnings and escalation
SLA timers flag a case when it is at risk and escalate it on breach, without waiting for a supervisor to step in.
Customer context on the case
The case holds the customer record, its history and the emails, texts and notes logged against it, so whoever picks it up starts with the whole story.
Live workload dashboard
Dashboards show work in progress, SLA risk and workload by agent and team in one view.
An email, text, portal request or phone call is captured as a case, or added to the customer's open case.
The case is prioritised by its type, the customer's segment and its SLA target.
The case is allocated to the best-fit available agent based on skills, availability, and current workload.
The agent sees the customer record, the case history, and any previous notes in one place.
If nobody suitable picks the case up within the SLA, it is flagged as at risk and escalated on breach.
Faster
Allocation to the right agent
Rules allocate each case as it arrives, so nobody has to sort a shared inbox first.
Fewer
Repeat contacts
The case keeps the history, so customers are less often asked to explain their issue again.
Automatic
Escalation on SLA breach
At-risk cases are flagged and breached ones escalated by rule, without a supervisor having to intervene.
Consolidate customer records, the knowledge base, and case management into a single agent interface, so agents spend less of each call alt-tabbing.
Contact centre agents often switch between several applications during a single interaction. Every alt-tab increases handling time, introduces data entry errors, and erodes the customer experience. New starters take weeks longer to become proficient because they must learn multiple disconnected tools.
Application switching
Agents alt-tab between CRM, telephony softphone, knowledge base, and ticketing systems dozens of times per call.
Duplicate data entry
The same customer details are keyed into multiple systems, increasing error rates and post-call wrap time.
Extended onboarding
New agents spend weeks learning disparate tools before they can handle live interactions confidently.
Single-pane agent workspace
Bring customer data, case history, and knowledge articles into one browser-based workspace.
CRM updates through the API
If you keep a separate CRM, we can connect SwiftCase to it through its API so updates are written back and details are keyed once.
Knowledge on the case
The case screen shows the knowledge base entries that apply to it, by workflow, status or client, so agents don't have to go looking.
Guided disposition codes
Post-interaction wrap is simpler with mandatory disposition fields that feed directly into reporting.
The agent picks up the next case from the queue, or opens the customer's case when they get in touch.
The case screen shows the customer record, previous interactions, open cases, and any pending actions.
The agent follows on-screen prompts, accesses knowledge articles, and updates case fields, all within the same view.
After the interaction, the agent completes mandatory disposition codes and any follow-up task creation in one step.
Shorter
Handling time
With customer data and the case on one screen, agents spend less of each interaction switching applications.
Faster
New-agent proficiency
A single interface with guided workflows gives new starters fewer tools to learn.
More
First-contact resolution
Knowledge on the case and the full case history help agents resolve queries without callbacks or transfers.
Automate QA scoring, calibration workflows, and coaching actions so evaluations are scored consistently and improvement plans are tracked to completion.
Many contact centres can only evaluate a small sample of interactions by hand. The sample is too small to be statistically meaningful, QA scores vary between evaluators, and the gap between evaluation and coaching feedback can stretch to weeks, by which time the agent has already repeated the same mistakes dozens of times.
Tiny sample sizes
Evaluating a small fraction of interactions means quality issues go undetected for weeks or months.
Scorer inconsistency
Different QA analysts interpret the same scorecard criteria differently, undermining agent trust in the process.
Delayed coaching
Weeks can pass between an interaction and the coaching session, reducing the impact of feedback.
No audit trail
Spreadsheet-based QA lacks version history and cannot demonstrate compliance to regulators or clients.
Configurable scorecards
Your scorecard is set up as a form on the evaluation, with the sections and questions you use.
Automated evaluation assignment
Evaluations are allocated across QA analysts by skill and current workload, so the load is shared fairly.
Calibration workflows
Several analysts can each evaluate the same interaction, so you can compare their scores and align standards.
Coaching action tracking
Automatically generate coaching tasks from failed evaluations and track completion through to sign-off.
QA trend reporting
Visualise quality trends by team, agent, question, and time period to pinpoint systemic issues.
Interactions are picked for evaluation by the rules you set, such as a complaint or a flag on the case.
A QA analyst completes the digital scorecard, with required fields and comments enforced by the form.
If the evaluation fails, a coaching task is automatically assigned to the agent's team leader.
The team leader delivers coaching, records notes, and the agent signs off, all tracked within SwiftCase.
QA managers review dashboards to identify recurring issues and adjust training programmes accordingly.
More
Interactions evaluated
Structured digital scorecards and automated assignment let QA teams get through more evaluations in the same time.
Faster
Evaluation-to-coaching cycle
Coaching tasks are created as soon as an evaluation fails.
Full
Audit trail of QA records
Each evaluation, calibration round, and coaching action is time-stamped and logged on the case.
Define clear escalation paths, automate tier routing, and track every escalated case to resolution, so no customer issue falls through the cracks.
When a frontline agent cannot resolve a query, the escalation process is often informal: a message in a group chat, an email to a manager, or a sticky note. Cases lose priority, ownership becomes unclear, and customers chase updates they never receive. For regulated services, untracked escalations create serious compliance exposure.
Informal handoffs
Escalations happen via email or chat with no structured tracking, making it easy for cases to be forgotten.
Unclear ownership
When multiple teams are involved, no single person owns the escalated case end-to-end.
SLA breaches
Without automated time tracking, escalated cases regularly breach internal and contractual SLA targets.
Tiered escalation paths
Define multi-level escalation routes (from team leader to department head to director) with automated triggers at each tier.
SLA countdown timers
Every escalated case carries a live SLA timer, with automated reminders and breach notifications sent to the case owner.
Automatic ownership assignment
Cases are assigned to a named owner at each escalation tier based on skill, availability, and current caseload.
Customer update automation
Trigger templated status updates to the customer at key milestones: acknowledgement, investigation, and resolution.
Escalation analytics
Report on escalation volumes, root causes, resolution times, and repeat-escalation rates by team and category.
An agent or automated rule triggers an escalation, capturing the reason, priority, and all interaction history.
The case is routed to the appropriate team leader or subject-matter expert based on category and skill match.
The case owner investigates, records findings, and takes corrective action, all within the case record.
Automated updates keep the customer informed at each stage, with the option for personalised messages.
The case is resolved, a root-cause category is recorded, and the case is closed with full audit history.
Fewer
Lost escalations
Every escalated case is tracked in a structured workflow with clear ownership and automated reminders.
Faster
Escalation resolution
Allocation rules and SLA timers get cases to the right person sooner and keep them moving.
Full
Audit trail coverage
Every escalation action, ownership change, and customer communication is logged for compliance and reporting.
Consolidate operational, quality, and commercial KPIs into automated dashboards and scheduled reports, giving every stakeholder the right data at the right time.
Contact centre managers spend hours each week pulling data from multiple systems into spreadsheets, reconciling figures that never quite match, and formatting reports for different stakeholders. By the time a report is delivered, the data is stale and the opportunity to act has passed. Client reporting is equally painful, with bespoke formats consuming analyst time that could be spent on insight.
Manual data consolidation
Analysts pull CSV exports from telephony, CRM, QA, and WFM systems and stitch them together in spreadsheets.
Stale reporting
Weekly or monthly report cycles mean decision-makers are always looking at outdated data.
Bespoke client formats
Each outsourcing client demands a different report layout, multiplying the effort for BPO operations teams.
One reporting layer
Report on cases, tasks, SLAs and QA evaluations in one place, with data from other systems brought in through the API or by import.
Management dashboards
Dashboards refresh automatically, showing KPIs such as work in progress, SLA performance and resolution times.
Scheduled report delivery
Configure daily, weekly, or monthly reports to be generated and emailed to stakeholders automatically.
Per-client report templates
Set up a report per client with the exact KPIs, layouts, and commentary fields they require.
Trend and variance analysis
Automatically highlight week-on-week variances and long-term trends so managers focus on what has changed.
SwiftCase brings its own case data together with anything imported from connected systems through the API.
Metrics are calculated using formulas you define, such as SLA performance, resolution time, or a bespoke KPI.
Dashboards update for supervisors and managers as the work moves.
At configured intervals, reports are compiled using the appropriate template and delivered via email or portal.
Less
Report preparation time
Automated data aggregation and scheduled delivery cut the manual spreadsheet work each week.
Current
Decision-ready data
Dashboards mean managers and supervisors act on current data, not last week's numbers.
Consistent
Client reports
Templated reports give each client the same accurate data on schedule without manual formatting.
Replace abandoned calls and manual callback lists with structured, SLA-tracked callback workflows, so customers are called back in the slot they chose by the right agent.
When callers abandon the queue or request a callback, the promise is often recorded on a spreadsheet or sticky note. Callbacks are missed, duplicated, or made at the wrong time. Each missed callback generates a repeat inbound call, inflating volumes and eroding customer satisfaction. For Ofcom-regulated outbound dialling, unstructured callback lists also create compliance risk.
Lost callback requests
Callbacks recorded in spreadsheets or emails are easily overlooked, especially during busy periods.
Wrong-time contact
Without scheduled slots, agents call customers at inconvenient times, reducing answer rates and satisfaction.
Duplicate outbound attempts
Multiple agents may attempt the same callback because there is no single source of truth for callback status.
Ofcom dialling compliance risk
Unstructured callback lists make it difficult to prove compliance with Ofcom persistent misuse regulations.
Structured callback queue
Every callback request enters a managed queue with customer details, preferred time, reason, and SLA deadline.
Time-slot scheduling
Customers choose a preferred callback window, and the system schedules the attempt within that slot.
Agent assignment rules
Callbacks are assigned to the original agent, a named case owner, or the next available skilled agent.
SLA and retry logic
Configure maximum attempt counts, retry intervals, and SLA deadlines with automatic escalation on breach.
Ofcom compliance controls
Set attempt limits and time-of-day restrictions as workflow rules, in line with your Ofcom policy.
A callback is requested via IVR, agent action, web form, or abandoned-call trigger, creating a structured callback record.
The system schedules the callback within the customer's preferred window and assigns it to the appropriate agent.
The agent makes the attempt, and the outcome (connected, no answer, voicemail, wrong number) is recorded.
If the customer was not reached, the system schedules a retry within configured rules. If connected, the case is resolved and closed.
Higher
Callback completion rate
Structured scheduling and retry logic help callback promises get kept within SLA.
Fewer
Repeat inbound calls
Completing callbacks on time cuts the follow-up calls customers make when promises are broken.
Full
Audit trail for Ofcom
Every callback attempt, outcome, and timing is logged for regulatory compliance demonstration.
Deliver dynamic, branching call scripts that guide agents through compliant conversations, adapting in real time based on customer responses and case context.
Paper-based or PDF scripts cannot adapt to what the customer actually says. Agents either read robotically from a linear script, annoying customers, or go off-script entirely, creating compliance risk. Updates to scripts require reprinting or redistributing documents, and there is no way to know whether agents are actually following the latest version.
Linear scripts ignore context
Static scripts cannot branch based on customer answers, forcing agents to hunt through irrelevant sections.
Version control chaos
When scripts are updated, there is no guarantee every agent is using the latest version.
Compliance exposure
Without enforced scripts, agents may skip mandatory disclosures required by FCA, Ofcom, or PCI DSS regulations.
Dynamic branching scripts
Build decision-tree scripts that branch based on customer responses, case type, and data pulled from CRM.
Mandatory compliance steps
Mark script steps as mandatory so agents cannot progress until required disclosures or verifications are completed.
Inline data capture
Embed form fields within script steps so agents capture data as they go, eliminating post-call data entry.
Centralised version management
Update a script once and it is immediately live for every agent, with no redistribution or retraining required.
Script adherence tracking
See which script paths agents follow and which steps take the longest.
The appropriate script is loaded automatically based on the interaction type, campaign, or queue the agent is handling.
The agent follows on-screen prompts, with the script branching dynamically based on their inputs and customer responses.
Mandatory steps (such as data protection statements or identity verification) must be completed before the agent can proceed.
Form fields within the script capture case data as the agent goes, writing directly to the underlying case.
The script concludes with a summary screen and disposition code, completing the interaction record.
Fewer
Compliance breaches
Mandatory script steps make it hard for agents to skip required disclosures or identity verification.
Shorter
Average handling time
Branching logic guides agents straight to the relevant path, so less time goes on searching through irrelevant script sections.
Instant
Script deployment
Script updates are live for all agents the moment they are published, with no reprinting or redistribution delays.
Hold each agent's working pattern, leave and skills in SwiftCase, so work is allocated to people who are in and you can see who has capacity.
Many contact centres still manage schedules in spreadsheets, relying on planners to manually balance shift patterns, holidays, training, and real-time demand changes. The result is chronic over- or under-staffing, excessive overtime costs, and agents who feel their preferences are ignored. When demand spikes unexpectedly, there is no systematic way to redeploy resources quickly.
Manual scheduling
Planners spend hours building and adjusting rosters in spreadsheets that lack demand-aware logic.
Over- and under-staffing
Without accurate forecasting, shifts are either overstaffed (wasting budget) or understaffed (breaching SLAs).
Adherence blind spots
Managers cannot see in real time whether agents are adhering to their scheduled activities.
Agent dissatisfaction
Rigid scheduling with no self-service options leads to high attrition in an industry already plagued by turnover.
Working patterns and rotas
Set each agent's recurring working hours and multi-week rotas, plus one-off extra shifts and leave.
Capacity and utilisation
See each person's capacity, booked time and utilisation over any period, so supervisors can spot who is overloaded.
Self-service availability
With the right permission, agents record their own working hours and leave, and allocation takes it into account.
Availability-aware allocation
Work is only allocated to people who are working and free, weighted by their current workload.
Working hours, rotas, and leave are set for each agent, by an admin or by the agent themselves.
SwiftCase works out each person's free time from their availability, leave, and existing bookings.
New work is allocated only to people who are available, weighted by their skills and workload.
Supervisors review capacity and utilisation by person and period to rebalance work.
One place
For rotas, leave and skills
Availability lives where the work is allocated, so planners have fewer spreadsheets to reconcile.
Fairer
Spread of work
Allocation weighs each person's workload and availability, so the busiest people are not handed more.
Clear
Capacity per person
Supervisors can see who has room for more work before the queue backs up.
Capture, track, investigate, and resolve customer complaints within a structured workflow that meets FCA, Ofcom, and client-specific regulatory requirements.
Regulatory bodies including the FCA and the Financial Ombudsman Service require firms to log, acknowledge, investigate, and resolve complaints within strict timeframes. Contact centres handling financial services, utilities, or telecoms calls must demonstrate a reliable complaints process with full audit trails. When complaints are tracked in spreadsheets or generic ticketing systems, deadlines are missed, root causes go unanalysed, and the organisation is exposed to regulatory action.
Missed regulatory deadlines
FCA rules require acknowledgement within set timeframes and final response within eight weeks; spreadsheets cannot enforce this.
Inconsistent categorisation
Without structured taxonomy, complaints are categorised differently by different agents, undermining root-cause analysis.
Poor audit trails
Regulators and clients expect a complete record of every action taken on a complaint, which is difficult to produce from email threads.
Regulatory-compliant workflow
Workflow stages (logging, acknowledgement, investigation, resolution, and closure) set up to follow FCA complaint handling rules.
Deadline tracking and alerts
Automatic SLA timers count down to acknowledgement and final response deadlines, with escalation on approaching breach.
Structured complaint taxonomy
Enforce consistent categorisation using configurable complaint types, root causes, and product/service codes.
Root-cause analysis reporting
Aggregate complaint data by category, product, team, and time period to identify systemic issues and trends.
Automated customer correspondence
Generate acknowledgement letters, holding responses, and final response letters from templates with merge fields.
The agent captures the complaint using a structured form with mandatory fields for category, product, and customer impact.
An automated acknowledgement letter is generated and sent to the customer within the regulatory timeframe.
The complaint is assigned to an investigator who reviews interaction recordings, case notes, and system data.
The investigator records the outcome, any redress offered, and generates the final response letter for customer sign-off.
The complaint is closed with a root-cause code and fed into trend reporting for continuous improvement.
Tracked
Regulatory deadlines
Automated timers and escalation rules keep acknowledgement and final response deadlines in view.
Faster
Complaint resolution
Structured workflows and automated task assignment cut the delays caused by manual handoffs.
Full
Audit trail for the FCA
Every action, communication, and decision is logged with timestamps and user attribution.
Run the payment steps around your DTMF masking service as a workflow, and collect the PCI DSS compliance evidence as you go, without slowing agents down.
Contact centres that take card payments are in scope for PCI DSS compliance. Agents who hear, see, or transcribe card numbers create data exposure risk. Call recordings that capture DTMF tones or spoken card details must be managed carefully. Without automated controls, organisations rely on agent discipline and manual pause-resume recording, an approach that auditors and acquirers increasingly reject.
Agent exposure to card data
Agents who see or hear full card numbers are a compliance liability and a social engineering target.
Recording management
Manually pausing and resuming call recordings during payment capture is error-prone and leaves gaps in QA coverage.
Audit evidence gaps
Proving PCI DSS compliance requires documented controls and evidence, which are difficult to produce from manual processes.
Scope creep
Without clear boundaries, the entire contact centre environment remains in PCI DSS scope, increasing audit cost and complexity.
Alongside your DTMF masking
Your DTMF masking service takes the card digits, so they go to the payment gateway without reaching the agent or the recording. We can connect it to SwiftCase through its API.
Secure payment workflow
Guide agents through your payment process with on-screen prompts at each step.
Compliance evidence collection
Log each payment interaction on the case with its timestamp and outcome for audit purposes.
Scope reduction documentation
Document network segmentation and data flow controls that reduce the PCI DSS scope of your contact centre environment.
Self-assessment questionnaire support
Generate evidence and control documentation that maps to PCI DSS SAQ requirements for your annual compliance review.
The agent starts the payment workflow from the case when the customer is ready to pay.
Your masking service suppresses the tones, so the card digits the customer enters go straight to the payment gateway.
The payment gateway processes the transaction and the result is recorded on the case.
The case is updated with the payment outcome and a timestamp, stored for audit.
Logged
Each payment interaction
Each payment follows the same workflow, with its outcome recorded on the case for audit.
Smaller
PCI DSS scope
With DTMF masking and network segmentation, the agent desktop and call recordings can come out of PCI DSS scope. Your QSA confirms what applies.
Less
Agent exposure to card data
With DTMF masking, agents do not see or hear the card number, which closes off a common social engineering risk.
Tell us the one process causing the most pain and we will tell you whether it fits a 30-day pilot, and what the scope and fixed price would be.
