Every question about HieCOR.
Find it in seconds.

HieCOR is a connected business operating platform for retailers and field service businesses. It connects retail sales, service work, customer communication, inventory, billing, scheduling, and AI-powered workflows in one system — replacing the fragmented combination of POS, CRM, billing, and communication tools most businesses currently run.

HieCOR is built for businesses that manage retail sales, service work, customer follow-up, parts, delivery, billing, and multi-step operational workflows — especially appliance, furniture, mattress, home services, field service, and retail-service hybrid businesses.

HieCOR eliminates the disconnection between sales, service, billing, customer communication, and reporting that comes from running multiple separate tools. It connects those workflows so every team works from the same customer and operational picture.

No. HieCOR is broader than a POS. It supports retail transactions, estimates, proposals, customer communication, work orders, scheduling, dispatch, billing, customer history, inventory, service reminders, review requests, and AI workflows.

Managers get a single view of customer activity, open work, follow-up status, service performance, operational exceptions, and team execution across the business — without pulling reports from multiple separate systems.

Yes. HieCOR connects sales, customer support, service, delivery, inventory, billing, and management workflows so every team works from the same customer and operational context.

Yes. A core design goal is to eliminate re-entry between systems — customer records, orders, service activity, communication, billing, and inventory are all connected so information entered once flows through the relevant workflows automatically.

Separate tools create gaps between sales, service, billing, communication, and reporting. HieCOR connects those workflows so teams always have the same picture — and data flows between departments without anyone manually passing it along.

Yes. HieCOR is designed around scalable business operations including multi-step service workflows, multi-location retail, customer engagement programs, team coordination, and AI-assisted task management.

Not necessarily. HieCOR can operate as the central workflow and operating platform while coordinating with other tools where specific integrations or legacy systems are already embedded in the business.

Estimates and proposals let sales teams build professional quotes with product options, service details, pricing, delivery requirements, and financing notes — and send them to customers for approval via text or email before the transaction is finalized.

Yes. The estimate-to-invoice workflow allows approved estimates to convert to a full invoice without re-entering any line items. All products, services, fees, and customer details carry over exactly as approved.

Proposals give sales teams a polished way to present options, show pricing, outline delivery and warranty details, and create a structured follow-up opportunity — rather than relying on verbal quotes that cannot be tracked.

Yes. Open estimates form a sales pipeline that managers can review to see which opportunities need follow-up, which are aging, and which are ready to close.

Yes. Customers receive a text or email with a link to a branded approval page. They can review, approve, ask a question, or download a PDF — from any device, with no login required.

Yes. Deposit collection is built into the approval step — the customer approves and pays the deposit in one action from the same approval page. The deposit is recorded and carries to the invoice automatically.

By organizing customer interest, quote activity, open estimates, and follow-up tasks so sales teams always know which customers need attention and when they last heard from your business.

Yes. Every location runs from the same customer records, product catalog, pricing rules, and reporting. When a customer buys at any location, inventory updates in real time company-wide.

After a sale closes, HieCOR triggers post-sale workflows automatically — delivery scheduling if applicable, a review request at the right interval, a warranty reminder from the purchase date, and a repeat purchase signal surfaced by AI.

Yes. HieCOR is designed for businesses where products, services, delivery, installation, warranty, and follow-up are all part of the same sale — so all of those elements can appear on one estimate and one invoice.

A service work order organizes the customer profile, equipment record, prior service history, diagnostic checklist, technician notes, evidence photos, parts used, estimate, customer approval, and payment — all connected in one field service record.

Technicians receive a full job brief before departure — the customer record, equipment details, prior service history, technician notes from prior visits, parts required, and access notes — all on their mobile device before they leave the shop.

Yes. HieCOR work orders use category-specific diagnostic checklists by job type. Every checkpoint requires a pass, caution, or fail status. The work order cannot close until all required checkpoints are completed.

Yes. Photos can be attached to individual diagnostic findings — timestamped, geotagged, and permanently stored on the work order and equipment record. Photos protect the business in disputes and build customer confidence.

HieCOR captures two distinct notes per finding — an internal technician note in technical language for the team, and a customer-facing explanation in plain language for the customer. Mark AI drafts the customer explanation from the technician note.

Yes. Failed diagnostic items convert to estimate line items with one tap — Mark AI suggests the most common parts and labor codes for the failure type. Parts availability is checked against live inventory before the estimate is sent.

Yes. The customer receives a branded approval link by text while the technician is still at the property — so most customers approve within 5 to 10 minutes and the technician leaves with a confirmed return visit booked.

Yes. The completed work order — checklist, findings, photos, notes, customer explanations, parts used, authorization, and payment receipt — is stored permanently on the customer and equipment record.

Yes. Warranty status and claim requirements are pre-loaded on the work order. The completed diagnostic, evidence photos, and parts list generate the warranty documentation package automatically.

Every future technician who opens that work order sees the full prior visit history — what was found, what was done, what parts were used, and any notes from prior technicians. They arrive prepared instead of starting from scratch.

HieCOR scheduling and dispatch connects the unassigned job queue, technician capacity, skill set matching, route sequencing, live job monitoring, customer notifications, and completion tracking in one dispatch board.

Jordan AI reads each unassigned job alongside each technician's current workload, zone, skill set, and parts on-hand. It recommends the best-fit technician for each job — the dispatcher reviews and confirms with one click.

Yes. HieCOR sends automated texts at every service milestone — appointment confirmation at scheduling, arrival window the morning of the visit, en-route notification when the prior stop finishes, and completion confirmation at job close.

Yes. HieCOR sequences each technician's stops by location, job duration, and customer time window. Jordan AI flags inefficient sequences and timing conflicts before the route is confirmed.

Yes. Jordan AI monitors every active job in real time and flags jobs running over expected duration, approaching a promised arrival window, or in a routing conflict — before the customer is affected.

Yes. Alex AI checks parts required for each job against the assigned technician's truck inventory and the nearest warehouse before dispatch. Shortages are flagged with time to resolve before the technician leaves.

Jordan AI identifies the closest available technician with the right parts and a gap in their schedule. The dispatcher re-routes with one drag on the board. The affected customer is notified automatically.

Yes. The dispatch board gives a single view of every technician's schedule, every active job, and every unassigned request across all zones — with Jordan AI surfacing conflicts and overloads before the day begins.

By sending automated arrival window texts before the visit, en-route alerts when the technician is on the way, and proactive delay notifications when a job is running late — before the customer has to ask.

Yes. Every service booking opens with the customer profile, equipment history, prior service visits, and warranty status already loaded. The dispatcher books the job with full context — no separate lookup required.

Yes. When a job is complete, HieCOR creates the invoice from the work order — pulling in the customer details, parts used, labor codes, and approved estimate items automatically. Zero re-entry between the work order and the invoice.

Yes. Technicians can collect payment by card tap, text-to-pay link, or QR code from their mobile device at the customer's door. Receipt is sent by text or email the moment payment is collected.

Alex AI compares parts logged on the work order against parts appearing on the invoice before it is sent. Any part used but not billed is flagged for review before the invoice goes to the customer.

Yes. Customer authorization and signature can be captured on a tablet at the door, via text link, or through the emailed invoice. The authorization is permanently stored and linked to the work order diagnostic for any dispute.

Commercial accounts can be invoiced with configured payment terms such as Net 30. HieCOR tracks due dates and sends automated payment reminders at configured intervals. Alex AI flags aging accounts before they reach collection status.

Yes. Warranty coverage deductions, commercial account pricing, promotional discounts, and customer-specific terms can all be applied during the invoice review step before the invoice is sent.

The billing dashboard shows every invoice status in real time — paid, open, overdue, and pending authorization. AI flags accounts approaching or past their due date for proactive follow-up.

Yes. When a technician logs parts on a work order, the parts are removed from truck inventory in real time and added to the invoice automatically — no manual reconciliation between parts used and parts billed.

Review request at AI-optimized timing, warranty reminder scheduled from the service completion date, and next service interval reminder configured for the job type — all triggered automatically from the paid invoice.

Yes. Every service invoice is linked to the corresponding work order diagnostic, evidence photos, customer authorization, and payment receipt — providing a complete documented record for any billing dispute.

2-way texting lets teams communicate with customers about appointments, quotes, service updates, delivery windows, reminders, billing, and follow-up questions — with every conversation logged on the customer record and every reply arriving in a shared team inbox.

Yes. When a customer message arrives, HieCOR automatically surfaces the matching customer profile, open orders, active service tickets, delivery status, and prior conversation history alongside the message.

Yes. HieCOR uses a shared team inbox where all customer messages are visible to authorized team members. Conversations can be assigned, needs-reply status is tracked, and no message falls through.

Service reminders are automated messages triggered by real service events — job close, warranty activation, delivery confirmation — that notify customers when it is time for maintenance, a filter change, a warranty check, or a follow-up service visit.

Consistent follow-up converts open estimates, reactivates lapsed customers, generates reviews, captures repeat purchases, and prevents customers from quietly going to a competitor — all from automated workflows connected to real transaction data.

Yes. When a customer replies to any follow-up message, the reply arrives in the 2-way inbox with their full purchase history, service records, and the original message thread already loaded.

By organizing all messages, reminders, and follow-up tasks in one inbox with needs-reply status, assignment, and AI-flagged urgency — so teams always know what needs a response and when.

Yes. HieCOR sends automated texts at delivery milestones — appointment confirmation, arrival window, driver en-route notification, and delivery completion confirmation — all triggered from the route and job records.

Yes. SMS reminders can include a reply call-to-action — customers can respond to book a visit, ask a question, or confirm interest — and the reply routes to the shared inbox with their full service context loaded.

Customers receive proactive updates at every milestone instead of waiting and wondering. Replies land in a shared inbox with context. Every interaction is logged so every team member sees the full conversation history.

Yes. HieCOR checks every completed job for unresolved service tickets, open disputes, complaint history in recent messages, and partial payment status before sending. Only customers with a confirmed positive completion receive the review request.

Yes. HieCOR sends review requests by SMS with a direct link to Google, Yelp, or your preferred review platform. The message is personalized with the customer's name, technician's name, and specific job type.

Morgan AI analyzes your historical review response data by job type, customer segment, and time of day — and sends each request at the timing that has historically generated the most responses for that customer type.

Taylor AI flags complaint-adjacent replies and routes them to the service manager with the full job record and customer history loaded — giving your team a chance to resolve the issue before the customer posts a public negative review.

Yes. HieCOR tracks the full review request funnel — sent, opened, link clicked, and converted — per technician, job type, and customer segment. Morgan AI surfaces the patterns that drive the highest conversion.

Yes. Review request performance is tracked per technician — conversion rate, response rate, and review volume. Morgan AI surfaces the timing and message patterns from top performers for the whole team to replicate.

A workflow ensures consistency, correct timing, complaint filtering, and tracking — whereas manually asking depends on the technician remembering and results in no visibility into what is working or why.

A stronger review profile attracts new customers, builds trust with buyers who research online before deciding, improves local search visibility, and increases the conversion rate of inbound inquiries.

Yes. The qualification step checks for unresolved issues before sending. Taylor AI also monitors post-service messages for dissatisfaction signals and routes them to the service manager proactively.

Most service businesses see review volume increase 3 to 5 times within 90 days of deploying HieCOR automated review requests — primarily because requests go to every qualifying customer, not just the ones the technician happened to ask.

Yes. HieCOR maintains a real-time inventory position per truck — updated every time a part is used on a work order or restocked from the warehouse. The dispatcher sees what is on every truck from the dispatch board before assigning a job.

Yes. Technicians log parts used directly from the work order on their mobile device. The part is removed from truck inventory in real time, the cost is applied to the work order, and the part appears on the customer invoice automatically.

Yes. Alex AI checks parts required for each job against the assigned technician's truck inventory and the nearest warehouse before dispatch. Shortages are flagged with resolution options — warehouse pull, truck transfer, or job reassignment.

Alex AI monitors every truck and warehouse inventory level in real time and compares current stock against usage velocity and the upcoming week's scheduled job types. Replenishment recommendations surface before stock runs out, not after a technician calls to report they have run out.

Yes. Transfers can be initiated from the dispatch board. Both inventory positions update in real time at the moment of transfer. Every transfer is logged for audit and reconciliation.

HieCOR tracks expected stock — based on restocks minus logged usage — and compares it against periodic physical counts. Alex AI flags discrepancies, missing parts, and trucks running below minimum levels before Monday morning dispatch.

When Alex AI flags a shortage before dispatch, the dispatcher can pull from the warehouse, transfer from another truck, or reassign the job — rather than sending a technician who arrives without the required part and has to reschedule.

Yes. Alex AI compares parts logged on the work order against parts appearing on the invoice and flags any discrepancy — protecting margin by ensuring every part that left the truck is billed to the customer.

Yes. From the replenishment recommendation, a purchase order can be created in one click — with the supplier, part number, quantity, and expected cost all pre-populated from the parts catalog.

Yes. Parts can be linked to equipment types, service categories, and diagnostic failure codes — so Mark AI can suggest the most likely required parts for a job based on the equipment model and the customer's reported issue.

HieCOR AI Employees are seven named, role-specific AI assistants built into the platform — each designed around a specific business function with access to your real customer, service, inventory, and transaction data.

Each AI Employee is built around a specific business role. They prepare recommendations, draft messages, flag exceptions, and surface opportunities using your real operational data — not generic responses to random questions.

Taylor is the Customer Support AI who manages inbound customer messages — drafting context-aware responses with full order history and service records loaded, flagging urgent conversations, and routing complaint-adjacent replies before they escalate.

Riley is the Product Data and Catalog AI who reviews product listings for completeness before they go live, standardizes attributes across channels, and flags missing images, weak descriptions, or inconsistent pricing before a customer sees them.

Jamie is the Sales and Customer Experience AI who identifies which customers are most likely to convert today, flags stalled quotes and estimates approaching expiry, and surfaces high-value customers who have gone quiet for follow-up.

Alex is the Inventory and Supply Chain AI who monitors stock levels across every location, flags below-minimum positions and oversell risks, surfaces replenishment recommendations from usage velocity, and catches parts used but not billed.

Jordan is the Field Operations and Delivery AI who prioritizes the dispatch queue every morning, recommends technician assignments based on location and skill, flags overrunning jobs in real time, and identifies route inefficiencies before departure.

Morgan is the Revenue Growth and Marketing AI who surfaces customers ready for follow-up, times review requests for maximum response rate, drafts campaigns from real customer and equipment context, and identifies winback and upsell opportunities.

Mark is the Service Technician AI who reviews scheduled jobs and surfaces the most likely failure path before departure, drafts customer-facing explanations from technician notes, suggests parts and labor codes, and flags deferred caution items for follow-up.

No. They support staff by preparing information, recommending actions, drafting messages, and reducing manual work — so your team focuses on the decisions and conversations that require human judgment.

Yes. The strongest results come from connected AI workflows — Morgan identifies a winback customer, Jamie flags the sales opportunity, Taylor monitors the incoming reply, and Mark checks the prior service history before the technician is dispatched.

By business outcomes — time saved on manual tasks, follow-up coverage rate, response speed, review volume, first-visit fix rate, parts billing accuracy, and revenue from customers who would otherwise have been missed.

AI matters because it reduces the manual work of checking, reminding, following up, and flagging — tasks that fall through the cracks in every busy operation — and replaces them with consistent, data-driven execution every day.

AI identifies high-intent customers, abandoned estimates, missed follow-ups, lapsed buyers, repeat purchase windows, review opportunities, and winback candidates — and surfaces them as ranked, actionable opportunities every morning.

AI reduces repetitive prep work, flags exceptions before they become problems, standardizes execution across the team, routes tasks to the right person, and improves workflow consistency without adding headcount.

AI uses customer history, equipment records, and communication context to recommend faster, more personal, and more consistent responses — so every customer feels like your team knows their situation.

AI reviews service tickets, summarizes customer history, identifies the most likely failure path, checks parts availability, and prepares technicians before arrival — increasing first-visit fix rates and reducing return trips.

AI connects data from customers, orders, inventory, service, and billing to surface patterns and exceptions that would take hours to find manually — making it easier for managers to act on what matters rather than searching for it.

Start with the highest-frequency, most manual workflows — review requests, follow-up reminders, dispatch assignment, parts checking, and invoice reconciliation. These generate immediate, measurable results and build confidence for broader adoption.

No. Any business with repeatable workflows, customer communication, service operations, inventory, or follow-up programs can benefit from AI — regardless of size. The value scales with operational complexity, not company size.

AI becomes valuable when it reduces the gap between what your team intends to do and what actually gets done consistently — follow-ups sent, parts checked, reviews requested, invoices reconciled, and exceptions flagged — every day without fail.

Yes. AI surfaces exceptions, summarizes activity, recommends priorities, and helps managers focus on the work that needs attention — rather than spending time finding out what is overdue, missing, or at risk.

Most businesses are live within 45 days. The US-based implementation team handles the full setup — customer data migration, product catalog, workflow configuration, payment setup, notification templates, and team training.

The US-based implementation team manages customer record migration, product and parts catalog setup, pricing rule configuration, payment method activation, notification template creation, dispatch and routing setup, and initial team training.

Yes. Training helps staff understand their workflows, where information lives, how AI recommendations work, and how to use HieCOR consistently. Training is structured by role — sales, service, dispatch, billing, and management each have different workflows.

The best approach is approval-based. AI prepares recommendations, messages, summaries, and next steps — staff review and approve the final action. Most AI-generated messages do not send automatically; they are queued for human review.

Yes. Access can be structured around roles — sales, service, support, dispatch, billing, management, and administration — so each team member sees only the workflows and data relevant to their responsibilities.

Track user adoption, reduction in manual tasks, faster response times, fewer missed follow-ups, improved first-visit fix rate, parts billing accuracy, review volume, and customer satisfaction scores.

Usually yes. The best results come when the business standardizes its core workflows — how jobs are created, how estimates are sent, how follow-up is triggered — and uses HieCOR as the shared operating system across teams.

Position AI as a support layer that reduces repetitive work and prepares information — not a replacement for employee judgment. The best adoption comes when employees see AI as making their job easier, not monitoring their performance.

Customer records, product catalog, service categories, parts inventory, pricing rules, communication templates, billing terms, and existing service history should be reviewed for accuracy before migration.

Use approved templates, configure review workflows, require staff approval for outgoing messages, set clear escalation rules, and structure role-based access for sensitive customer communication. AI prepares; humans approve.