SSAIB Approved Company Directory

Ssaib approved company directory data is the certified universe of UK and Irish security and fire safety firms behind the mark buyers look for when an insurer or a police force asks whether an installer is legitimate. The Security Systems and Alarms Inspection Board, a certification body headquartered in Whitley Bay, keeps a register describing every company it certifies, and SSAIB itself frames certification as the signal insurers and police forces rely on when vetting installers.

The register stacks two filters. Supplier categories - ten of them - split the market into Security Systems, Fire Detection and Fire Alarm Systems, Monitoring Centres, Security Services, Emergency Lighting Systems, Evacuation Alert Systems, Fire Extinguisher Service and Maintenance, Fire Risk Assessment, Investigative Services and Management Systems. Certification schemes go one level finer, roughly three dozen deep: intruder alarm systems, alarm receiving centres, CCTV systems including detector-activated CCTV to export standards, access control, key holding and response services, static guarding and mobile patrols, security screening, vacant property protection, ISO 9001 quality management and more.

Each entry carries the company's trading and registered names, full postal address, public contacts and its certification scope, and the Republic of Ireland runs as a distinct supplier list alongside the UK body of the register. Datadory normalizes all of it into one roster. Get a sample of this dataset - name the categories, schemes or regions you need and real rows come back before you commit.

One record per certified company, in the flattened shape a delivery arrives in:

trading_name    : <certified company>            registered_name : <legal entity>
category        : Security Systems               scheme : Intruder Alarm Systems
address         : <street, town, postcode>
telephone       : <public telephone>             email  : <public email>
website         : <company site>                 scopes : <certification scope detail>

trading_name    : <certified company>            registered_name : <legal entity>
category        : Monitoring Centres             scheme : Alarm Receiving Centres
address         : <street, town, postcode>
telephone       : <public telephone>             email  : <public email>
website         : <company site>                 scopes : <certification scope detail>

Read the two blocks side by side and the dataset's main job appears. Same field furniture, different category and scheme - which is the difference between the installer who fits an alarm panel in a semi and the alarm receiving centre that answers the signal when it fires. A third block would show a fire-detection specialist carrying matching category and scheme values, which is how single-discipline fire firms look in the register.

registered_name earns its keep on every corporate-development job: trading names rebrand while legal entities persist, and keeping both lets joins survive the rename. Your sample ships with populated rows for the companies you name, so the placeholder values above resolve before anything is signed.

Eight fields define every record, mapped from the structure the register exposes for each certified company. trading_name and registered_name fix identity twice over - the brand the market knows and the legal entity behind it. address locates the registered premises. telephone, email and website carry the public contact surface.

The certification payload is where the register gets interesting. supplier_category assigns one of ten market-wide categories; certification_scheme itemizes which of roughly three dozen schemes the firm actually holds, so a dual-discipline operator carrying both intruder alarm and CCTV certification shows up under both without splitting into duplicate identities. scopes states exactly what the certificate covers, and schedule_documents preserves the per-company certificate schedule material attached to the record.

Values observed during research but not yet pinned to named companies sit in the on-request tier below the table - ask for them in your sample and they arrive populated.

• Geography - the United Kingdom and the Republic of Ireland together, with the RoI running as its own supplier list. Cuts work at postcode-distance depth out to 10, 20 or 30 miles, by town, or across whole nations.
• Temporal - current certification status as published: a standing register of who holds certification now, not a historical archive of certificates past.
• Granularity - one record per certified company, spanning intruder alarm installers, alarm receiving centres, CCTV and access control firms, guarding and patrol providers, key-holding services, fire-safety specialists and investigative services firms.

The register spans thousands of certified firms; neither nation publishes a running total, which is precisely why a scoped sample helps - it returns the actual populated count for whatever categories, schemes and regions you name, converting an estimate into a number you own.

API, files, or your warehouse. Daily, weekly, or hourly.

You pick the channel and the cadence; the eight-field dictionary above travels unchanged through all of them. Rows arrive cleaned and typed - names separated from legal entities, addresses normalized, categories and schemes mapped to stable values - so vendor-vetting logic becomes a WHERE clause instead of a manual lookup habit. The set joins cleanly to firmographic tables on company name and geography, and to our NSI companion set when a job needs both certifiers' universes covered. Cadence changes are a settings conversation, not a re-integration project, and a scoped sample comes first either way. Get a sample of this dataset →

• Alarm distributor networks and monitoring stations qualify subcontracted installers across a whole bench at once - scheme, category and scope per firm rather than one manual lookup at a time.
• Insurers and risk desks document that contracted installers held certification at engagement - an auditable artifact rather than a screenshot.
• Private equity and corporate development teams map acquisition candidates across the UK and Irish installation base, using scheme holdings as a capability proxy.
• Compliance and procurement teams run automated checks that every vendor in the supply chain carries current certification for the exact service it sells.
• Market researchers and consultants size the installation, monitoring and fire-safety services market from its certified floor, segmented by discipline and region.

Deeper application notes sit on the competitive intel product teams, sales growth teams and market researchers pages.

Competitive intelligence and product teams get a clean read on rival capacity: which competitors hold monitoring-centre certification, which stick to intruder alarms, which have added fire scopes. Sales and growth teams turn the register into partner-recruitment territories without assembling spreadsheets town by town. Investors and quant researchers frame consolidation theses on a defined population of certified firms. Data scientists adopt the roster as the entity spine that incident, permit and firmographic files hang off. Developers and builders wire automated vendor-vetting into procurement flows on a schema that stays put. Across all six, the constant is the same: a register that answers “who is certified, for what, and where” completely beats a wider source that answers it vaguely.

Three things, all knowable upfront. First, the register is a point-in-time picture - “thousands of certified firms” is the honest description because no running count is published, and your sample returns the populated rows for whatever categories, schemes and regions you name. Second, coverage is the current certification state, so longitudinal questions need the snapshot series started now rather than retrofitted later. Third, the dictionary ships complete - eight fields mapped from the register's own structure - with observed example values settling at sampling instead of being promised blind. Scope your integration around the constants and let the sample fill in the specifics.