Faster routing, consistent decisions across every shift
Sphere's AI Dispatch Copilot sits alongside your dispatchers — not in front of them. It scores every call, recommends the right unit, and flags demand surges before they become SLA breaches. Integrated with your CAD system. No rip-and-replace.
Organizations around the world trust us
Dispatch Is a Data Problem Dressed Up as a Staffing Problem
Most agencies respond to dispatch failures by hiring more people or buying faster CAD software. But the root cause isn’t headcount — it’s the absence of a real-time intelligence layer between the incoming call and the dispatching decision.
1. Peak Load Overwhelm
Average emergency response times increase 40% when dispatch centers hit capacity during peak incidents, shift transitions, or multi-unit events. Cognitive overload leads to slower, less accurate routing — with direct safety consequences.
2. Manual Routing = Resource Misalignment
Manual call routing based on dispatcher memory and radio communication causes systematic misalignment. The wrong unit takes the call, the closest asset sits idle, and SLA windows close. Each misallocation carries contract penalties — and in life-safety contexts, irreversible cost.
3. Intuition-Driven, Inconsistent Outcomes
Dispatch decisions vary by dispatcher, shift, and experience level. Without a data layer, there’s no way to enforce consistent triage, no feedback loop, and no audit trail for SLA compliance.
An AI Copilot That Augments Every Dispatcher and Call
Sphere engineers the intelligence layer that sits between your CAD system and your dispatcher’s screen. The AI Dispatch Copilot ingests live call data, unit telemetry, historical incident patterns, and external demand signals to generate real-time recommendations — displayed as a non-intrusive overlay on your dispatcher’s existing workflow. Human judgment stays in command. AI ensures it is always informed.
Intelligent call routing
Route every call based on incident type, location, and real-time unit availability — not dispatcher memory.
- Matches incident to the right unit class automatically
- Factors in proximity, status, and skill match
- Replaces radio-based guesswork with data-driven selection
Real-time incident prioritization
Score every incoming call for severity and urgency so dispatchers always work the highest-impact incidents first.
- Priority score visible before intake conversation ends
- AI-ranked queue across all active calls
- Recommended response tier for each incident
Resource allocation recommendations
Surface the best available unit for each call — accounting for in-flight assignments and predicted demand.
- Optimal unit recommendation with confidence score
- Awareness of in-flight calls and shift transitions
- One-click override with full logging
Predictive demand forecasting
See call volume and incident type distribution 30–60 minutes ahead. Pre-position units before the surge hits.
- Forecasts with >88% accuracy on trained incident data
- Pre-positioning and overtime authorization alerts
- Prevents peak-load SLA collapses before they start
CAD integration, no replacement
Connects to your existing CAD platform via certified integrations. No workflow changes. No new system to learn.
- Tyler New World, Motorola PremierOne, CentralSquare, Hexagon
- Custom adapters for legacy and regional systems
- Live in 2–3 weeks, not 2–3 quarters
Compliance and post-incident analytics
Every decision, recommendation, and override is logged. Shift reports and SLA dashboards generated automatically.
- Automated audit trails for CALEA and CMS reviews
- Daily SLA compliance dashboards
- Override analysis and continuous model improvement
Outcomes
The best dispatch operations are moving from experience-based routing to real-time, data-informed decisions: score the call, match the unit, forecast the surge, log the outcome, and learn from every shift. Sphere's AI Dispatch Copilot is built for this shift — with human authority over every decision and AI making sure that authority is always informed.
Shorter call-to-dispatch times across peak and off-peak shifts
Fewer wrong-unit dispatches and mid-call reassignments
Higher SLA compliance, especially on Priority 1 response windows
Lower repeat-call and callback volume
Reduced overtime and manual reporting labor
Clear audit trail for accreditation, client SLA, and regulatory reviews
See the Copilot in action
A short walkthrough focused on your CAD platform and dispatch workflows.
Use Cases
Public Safety / 911 (PSAP Centers)
AI triage layer deployed across 4 consolidated PSAPs serving 1.2M residents. Call priority scoring reduces average dispatcher cognitive load by 34%. Demand forecasting eliminated 3 SLA breach events in first 6 months. Annual savings: $1.8M in avoided penalty payments and overtime labor.
Emergency Medical Services (EMS)
AI allocation engine integrated with regional EMS CAD (CentralSquare) serving 220 square miles. Closest-appropriate-unit accuracy improved from 71% to 94%. Hospital diversion routing model reduced diversion-related transport time by 19 minutes per event. Repeat-call rate dropped from 21% to 13%.
Fire & Rescue Dispatch
Predictive demand model pre-positions apparatus during identified high-risk windows (dry weather + high wind events, holiday periods). Sphere's integration with GIS and weather APIs enables automated pre-deployment alerts. First-unit on-scene time reduced 22% during modeled high-risk periods.
Private Security Operations Centers
AI copilot deployed across corporate campus SOC (12 dispatcher seats, 6 sites). Priority 1 SLA window (sub-4-min) compliance improved from 74% to 96%. AI-generated patrol scheduling reduced coverage gaps 41%. Client reporting fully automated: zero manual SLA documentation labor.
Healthcare / Non-Emergency Medical Transport (NEMT)
Scheduling AI replaced manual NEMT dispatch for a 300-transport/day operation. On-time pickup compliance improved from 71% to 94%, achieving CMS documentation requirements. Route optimization reduced fleet fuel costs 14%. Dispatcher headcount held flat despite 23% volume growth.
How it works: Sphere's 5-step deployment process
Discovery & CAD Integration Audit
Sphere's solutions architects conduct a 2-week technical discovery: CAD system assessment, API availability mapping, dispatcher workflow documentation, historical incident data audit, and AWS environment review. Deliverable: AI Dispatch Copilot Integration Blueprint (complimentary for qualified agencies; fixed-fee otherwise). No commitment required.
Data Ingestion & Model Training
Sphere's data engineers connect to your CAD system and ingest 12–24 months of historical incident, dispatch, and outcome data. Custom ML models are trained on your data — your incident types, your geography, your unit mix — not on generic industry datasets. Initial model accuracy validation target: >88% F1 on holdout incident set.
Copilot UI Configuration & Dispatcher UX Testing
The Dispatcher Assist overlay is configured to your CAD platform's screen layout, your dispatch protocols, and your terminology. Three rounds of dispatcher UX testing with your senior dispatchers. Recommendation display, confidence thresholds, and override UX are all configurable per agency policy.
Pilot Deployment (Human-in-the-Loop)
A 30-day supervised pilot on a subset of shifts with human-in-the-loop override tracking. AI recommendations are visible but not mandatory. Override rates, recommendation accuracy, and dispatcher feedback are reviewed weekly. Model is refined based on pilot outcomes before full rollout. All data stays in your AWS environment.
Full Rollout & Continuous Learning
Full agency deployment across all dispatcher seats and shifts. Automated retraining pipeline updates models monthly using new incident data. Operations manager dashboard provides real-time Copilot performance metrics. Sphere's AI acceleration retainer (optional) adds new capabilities each quarter and prepares the next CAD integration enhancement.
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ROI & Business Impact
27%
average reduction in call-to-dispatch time across Sphere Copilot deployments (50-dispatcher baseline, 6 months post-go-live)
40%
reduction in resource misalignment incidents – measured as wrong-unit dispatches requiring reassignment or cancellation within 8 minutes
$2.1M
average annual cost avoidance per 50-dispatcher center: avoided SLA penalties ($820K), reduced overtime ($640K), lower repeat-dispatch labor ($440K), and eliminated manual reporting ($200K)
ROI payback period:
11–16 months at $300K–$450K engagement; <10 months at $500K+
Hear from
our clientsHear from our clients
Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
Ben Crawford
Senior Product Manager at Enova Financial
I would expect to be delighted. It's been a really positive experience, working with Sphere, and I would expect you to have the same.
Mark Friedgan
CEO at CreditNinja
Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.
René Pfitzner
Co-Founder at Experify
Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.
Bruce Burdick
Chief Information Officer at Integra Credit
We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.
Jemal Swoboda
CEO at Dabble
The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.
Arthur Tretyak
Founder and CEO at IntegraCredit
With Sphere, we were able to migrate in half the time it would take to train an additional FTE… and for a fraction of the cost. Our experience with Sphere has been exceptional.
Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
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