CIS & Billing Platform

Enterprise billing &
customer operations
for energy utilities.

Utility billing software & customer information system (CIS) — meter-to-cash platform for electricity, gas, water, and district heating providers.

Replace your legacy CIS in months, not years. Billingly covers the full meter-to-cash cycle — from smart meter ingestion through complex tariff rating to multi-channel invoice delivery — in a single configurable platform. Launch new products, pricing models, and markets without writing code. Deploy on cloud or on-premises.

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The utility billing challenge

Why legacy utility billing systems fail modern energy companies

The energy industry is undergoing a fundamental transformation. For utility companies evaluating new billing software or replacing a legacy customer information system (CIS), the landscape has shifted dramatically. Deregulation, decarbonization, and digitalization are reshaping how utilities operate — and the legacy billing systems they depend on were never designed for this reality.

A typical energy company today manages customer data across six or more disconnected systems: CIS for contracts, MDM for meter data, GIS for location data, a separate billing engine, a CRM for customer service, and various external registries for business validation, property ownership, and regulatory compliance. Each system was procured independently, integrated with custom middleware, and maintained by separate teams.

The result? Service agents spend 30–40% of their call time navigating between applications. Pricing changes that should take hours require weeks of developer involvement. Adding a new product means coordinating changes across billing, product catalog, and rating engine — often duplicating configuration in multiple places.

Hundreds of business-rule customizations accumulate over a decade, turning what was once a standard platform into an unmaintainable monolith. The total cost of ownership escalates — not from license fees, but from the hidden cost of inflexibility: delayed market entry, manual workarounds, compliance gaps, and frustrated customers.

Billingly was built to solve this from the ground up: a unified platform where CIS, billing, CRM, and meter data converge in a single configurable system. Where pricing logic lives in business-user-editable formulas, not developer code. Where a new market launch is a configuration exercise, not a new implementation project.

⏱️

Fragmented client data

Customer information scattered across CIS, MDM, GIS, billing, CRM, and external registries. Service agents switch between 3–5 applications per call. Each screen switch adds 8–12 seconds to average handle time.

🔧

Custom development for every change

Adding a new product, adjusting pricing logic, or changing invoice templates requires developer involvement. Time-to-market for business changes: weeks instead of hours. Hundreds of custom modifications accumulated over years.

💸

Expensive implementation cycles

Traditional enterprise billing platforms require 6–18 months for initial deployment and millions in consulting fees. Every regulatory change, every new market entry triggers another costly project cycle.

🔗

Integration overhead

MDM data exchange, market operator messaging, e-invoicing, financial system export — each integration is custom-built and separately maintained. Ongoing maintenance cost often exceeds the initial development investment.

📋

Audit and compliance gaps

GDPR consent management, power of attorney tracking, financial audit trails, and regulatory reporting spread across multiple systems. Compliance verification requires manual cross-referencing that doesn't scale.

🌍

Multi-market limitations

Expanding to new countries means re-implementing: different tax rules, invoice formats, regulatory requirements, languages, currency handling. Each market becomes a parallel implementation project.

Utility CIS data architecture

Utility data model: from customer to meter in one platform

Most CRM platforms model customers as flat records with addresses and contacts. But energy distribution requires a far richer model — one that mirrors the physical infrastructure of the grid itself. A single corporate customer might operate across dozens of premises, each with multiple connection points, each with distinct technical parameters, each with one or more metering points identified by European-standard EIC codes.

Billingly's data model captures this hierarchy natively. At the top: the customer entity with identity, segmentation, and contact data. Below it: structured addresses linked to national land registry APIs for automatic geocoding and cadastral data retrieval. Then the premise point — a physical building or property. Within each premise: connection points with their electrical parameters (fuse size, voltage, phase count), where the platform uniquely tracks both the actual and contractual values side by side — enabling instant detection of discrepancies that affect billing accuracy.

At the leaf level: metering points with EIC codes, consumption type, production indicators, and electric heating flags. Each metering point is automatically linked to its parent connection point and premise, eliminating the manual data entry errors that plague legacy systems.

This hierarchy isn't just for display — it drives billing logic. Multi-connection-point premises (MCPP) are supported with umbrella contracts and sub-contracts, where capacity charges can be calculated either per connection point or aggregated across the entire premise. The model supports sub-premises for apartment buildings and commercial complexes, where individual units have separate metering but share common infrastructure.

Entity Hierarchy

Customer

Identity, EIC, segment, contacts, consents, powers of attorney

Location

Structured address, land registry API integration, cadastral data, coordinates

Premise Point

Building/property, name, status, type. Upper (building) + sub (unit) hierarchy

Connection Point

Fuse size (A), voltage (kV), phase count — actual vs. contractual values

Metering Point

EIC code, production type, electric heating flag, closure status

Meter / Sub Premise

Physical meter device, sub-premise unit, measurement type

📄

CIS

Contracts, service points, billing rules

📊

MDM

EIC codes, consumption, meter readings

🗺️

Address API

Geocoding, cadastral, coordinates

💰

Billing

Balances, references, entries

📞

CRM

Contacts, outage alerts, comments

🏛️

Registries

Business, property, GDPR consents

MDM & smart meter integration

Smart meter data integration & automated billing pipeline

Meter data from smart meters and advanced metering infrastructure (AMI) flows through an asynchronous, fault-tolerant pipeline from external meter data management (MDM) systems into the billing engine. The architecture uses S3-based staging, automatic retry with fallback to forecast values, and a ledger-based accounting model that tracks imported, uninvoiced, and invoiced quantities per metering point and period.

MDM System

Meter Data Management — external

↓

REST API request per EIC + period

↓

API Integration Layer

Validates, transforms, stages data

↓

JSON files staged to S3

↓

S3 Staging Area

Async buffer — organized by import batch & period

↓

File detection triggers import

↓

Ledger Engine

Per-EIC accounts: imported → uninvoiced → invoiced

↓

Readings ready for billing

↓

Billing Engine

Combines fixed charges + consumption + corrections

↓

Invoices

Financial Entries

Accounting Export

⟳ Correction Loop

When MDM sends correction notifications for past periods, they are staged in S3, imported into separate Ledger correction accounts, and automatically included in the next billing run — adding correction line items to current-month invoices.

How meter data reaches the invoice

When a mass billing run is initiated — either on schedule or manually — the system identifies all billing commands for the period and determines which metering points need consumption data. For each EIC code, a REST API request is sent to the external MDM system, specifying the billing period.

The MDM system returns reading data asynchronously. Responses are staged as JSON files in an S3 bucket, organized by import batch and timestamp. A file detection service monitors the bucket and triggers automatic import into the Ledger — Billingly's built-in financial accounting engine that maintains separate accounts for each metering point and data type.

The Ledger tracks three states for every quantity: imported (received from MDM), uninvoiced (ready for billing but not yet on an invoice), and invoiced (already billed). This triple-entry model prevents double-billing and enables precise audit trails.

If data doesn't arrive within the expected window, the system retries at 24–48 hour intervals, up to three times. If readings are still missing, the MDM may return forecast values. If even forecasts are unavailable, the reading is marked as missing and flagged for manual review.

Corrections are handled through a fully automated loop. When the MDM system revises historical consumption data — due to meter recalibration, delayed readings, or data quality fixes — it generates correction notifications. These are staged in a dedicated S3 directory, imported into separate Ledger correction accounts, and picked up during the next billing run. The billing engine detects that corrections exist for a given EIC, fetches the revised data for the correction period, and generates additional line items on the current month's invoice showing both the original and corrected amounts.

Tolerance parameters — day tolerance, night tolerance, 24h tolerance, and maximum throughput tolerance — are configurable through the admin interface and applied by the billing formulas to determine whether a correction warrants an invoice adjustment.

Billing corrections automation

Automated meter data corrections & billing adjustments

When meter data for a past billing period is revised — due to recalibration, delayed readings, or data quality fixes — the platform handles the entire correction lifecycle automatically. No manual intervention, no separate correction runs, no risk of double-billing. Corrections are detected, imported, calculated, and invoiced as part of the standard billing cycle.

1. MDM sends a correction notice

A revised period arrives for a metering point with the EIC code and corrected time window.

2. The platform stages and imports it

The correction file is stored, detected automatically, and imported into dedicated correction accounts.

3. Billing run picks up the revision

The engine finds the revised period, compares original and corrected values, and prepares the delta.

4. Customer sees a clear invoice adjustment

The current invoice shows both the reversal and the corrected line, keeping the audit trail intact.

CIS & billing platform modules

Utility CIS platform: six integrated modules

Each module addresses a specific domain of utility operations. Together, they eliminate the integration overhead and data fragmentation that plague multi-vendor architectures.

👤360° client card with 12 specialized sections

Customer Information System

A unified client card that aggregates identity, contacts, contracts, premises, connection points, metering points, reference numbers, powers of attorney, comments, properties, and GDPR consents from six different data sources into a single navigable view. The left-side menu shows all sections with record counts — one glance tells you what data exists and what's missing.

Person & customer management

Separate person and customer entities allow one individual to hold multiple customer roles. Business and private customers, registry codes, EIC identifiers, segmentation, account manager assignment.

Multi-channel contacts & addresses

Email, phone, SMS contacts with preference flags and expiry dates. Structured addresses linked to national land registry APIs for automatic geocoding, cadastral unit codes, and coordinate data.

Outage notification contacts

Separate contact section specifically for outage notifications — independent from regular contacts. Mandatory for regulated energy distributors to ensure notification delivery during planned and unplanned outages.

Powers of attorney

Bidirectional: who represents the customer, and whom the customer represents. Type (full authority, limited), validity period, status (active/expired), source. Instantly visible during customer service interactions. The same authorization model extends to API access — enabling self-service portals, brokers, and third-party representatives to operate within scoped, time-bound delegations.

GDPR consent management

Consent types, validity periods, granting channels. Integrated into the client card rather than a separate system — service agents see data processing restrictions in the same view where they work with customer data.

Properties & ownership

Land registry and property register data directly on the client card. Property ownership verification without external registry queries — a prerequisite for many service operations in regulated utilities.

🏗️Premise → Connection Point → Metering Point → Meter

Network Infrastructure Hierarchy

A four-level hierarchy that models the physical reality of energy distribution infrastructure. Each level carries specific technical and business meaning that drives contract logic, billing calculations, and outage management. The hierarchy supports multi-connection-point premises (MCPP) with umbrella contracts.

Upper & sub-premises

Upper premise = physical building or property. Sub-premise = apartment, commercial unit, heat node within a building. Essential for apartment buildings, business parks, and industrial complexes where billing granularity matters.

Connection points with dual parameters

Physical connection attributes: fuse size (A), voltage (kV), phase count. Each parameter shows both actual and contractual values side by side — enabling instant detection of discrepancies that affect billing accuracy and grid losses.

Metering points with EIC codes

European-standard EIC code identification, production type flags, electric heating indicators, closure status. Automatic linking to parent connection points and premises eliminates manual mapping errors.

MCPP support

Multi-Connection Point Premises: umbrella contract + sub-contracts per metering point. Capacity charges calculated either per connection point or aggregated across the entire premise. Per-metering-point supplier management.

📄From draft through versioning to termination

Contract Lifecycle

Complete contract lifecycle management with state machine logic: draft → offer → signing → active → in termination → terminated. Contract activation automatically generates billing commands based on product packages and metering points. Versioning preserves full history while seamlessly transitioning billing rules.

Contract portfolio

Contract number, reference number, status, type (primary, self-consumption, low voltage), validity period. PDF document download for each contract. Active/cancelled/terminated filtering.

Automatic billing command generation

When a contract is activated, the system automatically creates billing commands based on the package products and associated metering points. The process is idempotent — reprocessing the same contract version does not create duplicate commands.

Versioning

Contract modifications create new versions. Previous version billing commands are terminated; new ones are generated automatically. Contact data and excise duty settings carry over to the new version.

Supplier switching

Automated processing of electricity supplier change messages. Hourly polling for new messages, daily batch processing. Billing rules updated automatically based on supplier segment and service type. UI-initiated switches processed immediately.

💰Mass billing, corrections, multi-channel delivery

Billing & Invoicing Engine

A highly automated billing engine that supports mass invoicing of hundreds of thousands of invoices per billing run. But automation alone isn't the differentiator — it's the depth of logic the platform handles without custom code. Each product's billing behavior is defined by an expression-language formula that can query ledger balances, process multi-period corrections, apply tolerance thresholds, and generate complex invoice line structures. When regulators introduce a new tariff model or marketing launches a product with pricing logic that didn't exist yesterday, the formula is updated — not the platform.

Mass billing

Automated periodic billing combining fixed charges, consumption-based products, and corrections. Stage-by-stage generation ensures integrity. Resume capability — if a session is interrupted, the next run picks up where it left off.

Invoice groups & reference numbers

Flexible invoice grouping logic with easy merging and splitting. Unique reference numbers per invoice group, generated according to national standards. Invoice group exclusions via file upload, manual entry, or API.

Multi-channel delivery

Invoice delivery via email, paper, e-invoice. Channel configurable per invoice group. SMS notifications. Invoice re-delivery. Multiple recipients per invoice group.

One-time charge import

Multiple input methods for non-recurring charges: file-based import (spreadsheets, structured data files), manual entry through the UI, or direct API submission. Creates new invoices or appends to existing pending invoices. Product and invoice group validation with error logging across all input channels.

Non-network service corrections

Dedicated correction worksheet for adjusting non-network service prices across a billing period. Creates corrective invoices that reference originals — original invoices remain unmodified, preserving full audit trail.

Advanced formula engine

The billing engine runs on a full expression-language formula system where every product's pricing, correction, and invoice-line logic is defined as a configurable formula — not hardcoded business rules. A single formula can identify the metering point from the billing rule, query ledger balances across multiple reading types and periods, distinguish between regular billing and corrections from different data sources, apply configurable tolerance thresholds to decide whether a correction warrants an invoice adjustment, and generate precise invoice lines including reversal of previously billed amounts and new corrected values — all automatically. This means any combination that marketing, regulation, or market conditions can devise — multi-connection-point capacity aggregation, dual-source correction logic with tolerance filtering, reactive energy split billing, prosumer net settlement — is handled by formula configuration, not platform development. When regulations change or a new tariff structure appears, a business analyst updates the formula; no developer sprint, no release cycle, no deployment risk.

🏦GL account mapping, revenue recognition, receivables, and real-time balance APIs

Finance & Accounting Engine

Billingly includes a full-featured financial accounting engine — not just balance tracking, but a professional-grade chart of accounts mapping system that automatically generates correct GL entries for every transaction. Each product and service type is mapped to specific debit/credit account pairs, with rules that differentiate between internal and external clients, VAT-liable and VAT-exempt scenarios, and multiple revenue categories. When an invoice is confirmed, the system generates granular accounting entries per invoice line — reactive energy, grid connection fees, throughput capacity charges, monthly fees, and metering services each flow to their designated revenue accounts automatically.

GL account mapping rules

The core of the accounting engine is a configurable account mapping table. Each product or service type maps to a specific pair of general ledger accounts — a revenue account and a corresponding receivable account. Mappings are rule-based: the same product can route to different GL accounts depending on client classification (internal vs. external), VAT status, or business entity. This eliminates manual journal entries and ensures every invoice line posts to the correct accounts from the moment of confirmation.

Revenue account granularity

Revenue recognition is broken down by service category: electricity energy, distribution fees, grid connection charges, throughput capacity, reactive energy, metering system fees, and monthly fixed charges each have dedicated account pairs. This level of granularity enables finance teams to produce detailed revenue breakdowns by service type without post-hoc reclassification — the data is correct at the point of entry, not reconciled after the fact.

Multi-entity and client classification

Account mapping rules support multi-entity setups where the same platform serves multiple legal entities. Revenue accounts differentiate between internal clients (without VAT) and external clients (with standard VAT rates) automatically. When an invoice is generated for a joint billing scenario — where one invoice covers services from multiple suppliers — each line routes to the correct entity's revenue accounts independently.

Automated financial entry generation

Every monetary transaction generates structured accounting entries automatically. Invoice confirmation creates VAT entries, revenue entries, and claim entries as a single atomic operation. Payment receipt creates corresponding payment entries. Credit notes, prepayment applications, and write-offs each generate their own entry patterns according to pre-configured rules — no manual bookkeeping required.

Payment matching engine

Incoming payments are automatically matched to invoices by reference number. When reference numbers don't match — a common reality during data migration or with legacy payment systems — the engine falls back to amount-based matching using invoice totals, dates, and customer identifiers as supporting criteria. Unmatched payments are flagged for manual review.

Reference-number-based balances

Every invoice group carries a unique reference number, and the system maintains running balances at this level. This enables per-contract, per-service-point, or per-customer balance views. Self-service portals and API consumers can query balances in real-time — total debt, prepayments, and net balance are available as separate components for flexible display.

Aged debt reporting

Built-in aged receivables reporting with configurable aging buckets (7, 15, 30, 60, 90, 180, 360+ days). Reports can be grouped by customer, by reference number, or by invoice group — enabling both high-level portfolio views and granular contract-level analysis. Exportable to Excel for external audit and finance team workflows.

Balance API for self-service

Dedicated REST API for balance queries, designed for self-service portal integration. Query all reference numbers for a customer, or drill into a specific reference number. Response includes aged breakdown, prepayments, total debt, and net balance. The same API serves both internal customer service tools and external self-service portals.

🔌API-first architecture with comprehensive coverage

Integrations & API

Every business operation in Billingly is accessible through REST APIs — customer, contract, premise, connection point, metering point, invoice, billing command, ledger transaction. The platform is designed for integration-first deployment, with pre-built patterns for MDM, financial systems, self-service portals, document management, and notification orchestration.

Complete REST API

Full CRUD operations + search across all business entities. API-first design means the UI and external integrations use the same endpoints. Comprehensive documentation and consistent patterns.

Self-service portal APIs

Dedicated API layer for customer-facing self-service portals and third-party integrations. Built-in delegation model: authorized representatives — such as energy brokers, property managers, or accounting firms — can act on behalf of the customer within defined scopes and time-bound validity periods. Delegations specify exactly which operations the representative may perform (view invoices, modify contracts, manage metering points) and automatically expire when the authorization period ends. The same model supports power of attorney scenarios where one organization represents another for billing, contract, or service operations.

MDM integration

Asynchronous consumption data pipeline via S3 staging. EIC-based metering point identification. Automatic retry with forecast fallback. Correction handling with separate ledger accounts.

Address registry API

Integration with national land registry APIs for structured address validation, geocoding, cadastral data retrieval, and property ownership verification. Automatic address enrichment on entry.

Financial system export

Pre-mapped GL entries from the accounting engine are exported automatically to external accounting systems. Consolidated financial transactions, VAT declaration base data, and revenue breakdowns by service category are sent in structured format. Export rules are configurable per legal entity, ensuring multi-company setups produce correct entries for each organization's general ledger.

Audit & logging

Structured Parquet-format logs in S3. User activity audit with correlation IDs across all system operations. Log viewer UI with filtering by dataset, time range, and user. Full compliance audit trail.

Notification orchestrator

Multi-channel notification delivery: email, SMS, automated calls, paper. Invoice delivery status tracking. Payment reminder automation. Debt notice generation and delivery.

AI-powered billing intelligence

AI-powered utility billing analytics & reporting

Billing data contains answers to every operational question a utility faces — which invoices have anomalous amounts, which metering points show consumption patterns that don't match their connection parameters, which customer segments have rising debt concentrations, which correction cycles are generating the most adjustments. The problem is that extracting those answers traditionally requires a reporting specialist who knows SQL, understands the data model, and has time to build the query.

Billingly's AI reporting assistant removes that bottleneck. A billing specialist, customer service agent, or finance manager types a question in plain language — "Show me all invoices from March where the correction amount exceeded the original charge by more than 50%" or "Which metering points on contract group 4821 had zero consumption for three consecutive months?" — and the system generates a precise SQL query against a purpose-built reporting dataset, executes it, and returns structured results. No report templates to configure, no IT tickets to file, no waiting.

The AI doesn't guess — it understands the billing domain model: contracts, billing commands, products, metering points, invoice lines, corrections, ledger accounts, reference numbers, invoice groups. It knows that a "correction" means a reversal line plus a new line, that "unpaid" means totalDebt minus prepayments, that a "connection point discrepancy" means actual fuse size differs from contractual. This domain awareness is what makes the difference between a generic chatbot and a tool that billing professionals actually trust.

The result: billing teams that previously waited days for custom reports now get answers in seconds. Anomalies that would have gone undetected for months are caught in the next query. Customer service agents can investigate a customer's full billing history — corrections, consumption trends, balance movements — without escalating to a specialist. Finance managers can drill into aged receivables by any dimension without pre-built report templates.

Privacy-by-design architecture

How it works — without exposing personal data

The AI model never sees raw customer data. Instead, it operates on a purpose-built reporting dataset where personal information is either excluded or reduced to opaque identifiers. The AI's only job is to translate a natural-language question into a SQL query — it generates the query, the platform executes it internally, and results are returned to the authorized user. No customer data is sent to external AI services.

Data classification in the reporting dataset

✗

Customer names

Never stored in the reporting dataset

◐

Personal ID codes

Anonymized format — structure preserved, values masked

→

Customer ID

Opaque reference only — no meaning outside the platform

→

EIC codes, reference numbers, company codes

Present for operational queries — required for billing analysis

Security & compliance

Built following Security and Privacy by Design principles. Data never leaves the platform boundary — the AI generates SQL, not data extracts. Role-based access controls determine which users can query which datasets. Full audit trail of every query generated, executed, and viewed. Compatible with GDPR data protection impact assessment requirements.

Example queries

"Show all invoices from January where correction lines exceed €50"

→ Billing error detection

"Which metering points had zero consumption for 3+ months but active contracts?"

→ Revenue leakage detection

"Aged receivables over 90 days, grouped by customer segment, this quarter"

→ Finance portfolio analysis

"Connection points where actual fuse size exceeds contractual by more than 5A"

→ Grid loss reduction

"Full billing history for reference number 39889 — invoices, corrections, payments, balance"

→ Customer service deep dive

"Compare average consumption per MCPP premise vs single-point premises this year"

→ Product & portfolio analytics

CIS software comparison

Utility CIS software comparison: Billingly vs Oracle, SAP & more

The utility CIS and billing market spans heavyweight ERP-embedded solutions to purpose-built platforms. This comparison focuses on the dimensions that matter most in procurement evaluations: deployment speed, client view architecture, and configurability without development.

Platform	Stack	Deployment	Client View	Configurability
Oracle CC&B	Java / WebLogic / Oracle DB	12–18 months	Multi-screen navigation; service points, accounts, contacts in separate views. SOA integration layer required.	Highly customizable but requires Java development resources for every change. Configuration is technical.
SAP CR&B / S/4HANA	ABAP / SAP HANA / Fiori UX	6–18 months	Fiori UX improved usability, but client picture remains distributed across SAP modules with CRM, CIS, and billing separated.	Configurable via Fiori, but ERP-centric constraints apply. ABAP competence is required for deeper changes.
Fluentgrid CIS+CRM	Java /.NET enterprise stack	Project-based	SaaS CIS and CRM modules with client view. AI integration in development phase.	Standard CIS solution; customization is project-based. MDM and GIS require separate integration work.
Cerillion BSS	Java SOA / cloud or on-prem	3–12 months	Convergent CRM view, but the primary focus is telecommunications, not utilities.	Configurable kernel with CI/CD support. Utility-specific features are more limited compared to telco.
Billingly	Cloud-native / API-first	30–60 days	Unified client card with 12 sections. Left-side menu navigation with record counts. All data on one page.	Expression-language formula engine handles all pricing, correction, and invoice-line logic. Business analysts modify tariffs, tolerance thresholds, and product behavior directly — no developer involvement. New regulatory requirements become formula updates, not platform releases.

Based on publicly available product documentation from Oracle, SAP, Fluentgrid, and Cerillion. Deployment timelines are typical estimates and depend on project scope.

Multi-utility billing software

Billing software for electricity, gas, water & district heating

⚡

Electricity Distribution

Full DSO workflow: connection points, fuse sizes, EIC codes, supplier switching, outage management, MCPP support, and excise duty tracking.

🔥

Gas Distribution

Gas metering points, consumption-based billing, multi-commodity customer view, and gas-specific product configuration and pricing.

🏭

District Heating

Heat metering, degree-day calculations, seasonal billing adjustments, building-level aggregation, and sub-premise metering support.

💧

Water Utilities

Water meter readings, sewage calculations, fixed and consumption-based billing, and meter replacement workflows.

🌍

Multi-Market Deployment

Multi-currency and multi-language support with country-specific tax rules, invoice formats, and regulatory compliance for configuration-based expansion.

🔌

Energy Retailers

Supplier switching integration, joint invoicing, self-billing, and partner billing with configurable revenue-sharing models.

99.9%

Platform uptime

<2s

Page load time

600K+

Invoices per run

200

Concurrent users

Markets supported

ISO 27001

Security compliant

Platform capabilities

Cloud-native, horizontally scalable architecture

Complete REST API for all business operations

AI-powered natural language reporting with privacy-by-design

Dedicated self-service portal APIs with delegation authorization

Chart of accounts mapping engine with per-product GL rules

S3-based asynchronous data pipeline for meter data

Built-in Ledger engine with period-based tracking

Expression-language formula engine with no-code pricing logic

Parquet-based structured audit logging

Role-based access control with module-level permissions

Multi-company, multi-currency, and multi-language support

Integration ecosystem

RESTful APIs with comprehensive documentation

MDM integration via S3-based asynchronous pipeline

National address registry API integration

Time-bound delegation model for third-party API access

E-invoice delivery with multi-channel support

Financial system export for GL-mapped entries and VAT data

Pre-built connectors for Amazon S3 and SQS

eTOM and TM Forum process standard alignment

GDPR compliance with EU-only data residency option

Ready to replace your legacy utility billing system?

See how Billingly replaces fragmented utility billing software with a unified CIS platform — meter-to-cash automation, configurable tariff management, and AI-powered reporting in one system. 30–60 day deployment. No custom development required.

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SaaS or on-premises deployment · API-first utility CIS · 30–60 day implementation

FAQ

Questions utilities and energy retailers ask before they modernize billing

This section gives search engines and AI tools clear, crawlable answers about what Billingly does, who it is for, and how modern utility billing workflows work.

What is a utility billing platform?

A utility billing platform is software that helps utilities and energy providers manage customer accounts, contracts, meter data, tariffs, invoices, payments, and service workflows in one system.

How does recurring billing work for energy providers?

Recurring billing for energy providers combines customer contracts, meter or usage data, tariff logic, billing cycles, invoice generation, collections, and customer communication into a repeatable automated process.

What is MDM in the context of utility billing?

MDM stands for meter data management. In utility billing it is the process and system used to collect, validate, store, and distribute meter readings so billing and customer service workflows use accurate consumption data.

Enterprise billing &customer operations for energy utilities.