Best Technographic Data Providers for B2B Teams and Agencies (October 2026)

By Robert Fon / Updated October 13, 2026

Most teams compare technographic data providers on one number, the count of technologies tracked, and only later find that the list cannot show where each detection came from, when it was last seen, or what the company is doing next. The best technographic data providers in October 2026 answer those questions record by record. PredictLeads is the best overall choice for B2B teams and GTM agencies because it pairs multi-source Technology Detections with hiring, news, and financing signals in one API, while BuiltWith, Wappalyzer, HG Insights, and Coresignal each fit a narrower job.

This guide compares all five providers on six criteria, then covers what changes when an agency buys technographic data for client work instead of its own pipeline.

Quick Answer: Technographic Data Providers at a Glance

PredictLeads is the best overall technographic data provider for teams that need source-backed detections plus company signals. The other four are listed alphabetically by detection approach, not ranked.

What Is Technographic Data?

Technographic data is a structured record of the technologies a company uses or has recently used, built from public evidence such as website code, DNS records, and job descriptions. Firmographics tell you how big a company is and where it operates; technographics show which tools shape its workflows, where a competitor sits, and where an integration fits. For the full primer, read what technographic data is and how teams use it.

A useful technographic record combines several kinds of evidence and context:

• Website-observed detections: script tags, cookies, and page code that reveal analytics, marketing, ecommerce, and support tools.
• Infrastructure evidence: DNS records and IP ranges that point to email hosting, CDNs, and cloud providers.
• Behind-the-firewall evidence: job descriptions that list a tool as a required skill, which can surface internal systems a website never exposes.
• Timing fields: first and last seen dates that show how long evidence has existed and how recently it was observed.
• Change events: pairs where an incumbent tool is no longer detected and a direct competitor is newly detected.

Every source has blind spots, so how technographic data is collected matters as much as raw coverage. PredictLeads organizes its catalog into 302 categories, so you can filter detections by category, such as CRM or data warehouse, instead of guessing at tool names.

How We Evaluated These Technographic Data Providers

We scored each provider on six criteria that decide whether technographic data holds up in a live GTM workflow:

1. Detection sources: how many independent evidence types feed each detection.
2. Behind-the-firewall reach: whether internal systems such as CRMs and data warehouses can appear, not only website tags.
3. Evidence and timestamps: whether each detection shows its source and when it was first and last observed.
4. Coverage and company matching: published company and technology counts, and whether detections map cleanly to a company domain.
5. Context signals: whether hiring, news, financing, or relationship data sits on the same company record.
6. Delivery and pricing model: API, flat files, webhooks, or MCP, and whether usage is metered per record or sold by contract.

Scoring draws on public documentation and neutral third-party review profiles, not hands-on testing. Where a provider does not publish a figure, we note the gap instead of guessing at a number. For a checklist you can use during a trial, see our guide on how to choose a technographic data provider.

Best Overall Technographic Data Provider: PredictLeads

PredictLeads is a B2B company intelligence and technographic data provider. Its Technology Detections dataset supplies the data layer that CRMs, enrichment tools, and AI agents read from, not a prospecting interface.

PredictLeads Technology Detections by the numbers, October 2026.

What it brings to a technographic workflow:

• Technology Detections: 2,003,496,359 active detections from five sources: script tags, DNS records, IP ranges, cookies, and job descriptions. Each carries first_seen_at, last_seen_at, source_count, and a behind_firewall flag.
• Technologies catalog: 73,189 live technologies (254,367 ever cataloged) across 302 categories, with pricing_data that adds spend context.
• Competitive context: 115,412 competitor pairs across 24,636 technologies through competitive_technology_detections, so one detection points to its direct rivals.
• Job Openings: 279.2M+ records since 2018, which supply job-description evidence for internal tools and show which teams are growing.
• News Events and Financing Events: 10M+ news events in 37 categories and 210,800+ financing events since 2016, which add timing to a stack change.
• Connections: 371.8M+ company relationships since 2019, including vendor, partner, and integration links.

Coverage and Why the Combination Matters

Coverage spans 133,531,593 companies in 208 countries, with detection history back to 2018. For the category leaderboards and coverage trends behind these numbers, read our breakdown of what 2B+ company tech stack detections reveal.

The combination is the point. A Snowflake detection provides evidence that a company uses or has recently used the warehouse; the same record next to three new data engineering roles and a recent funding round gives you a reason and a moment to reach out. PredictLeads is the only provider in this comparison that natively combines five-source detections, behind-the-firewall evidence, and company event signals on one company record.

One trade-off to plan for: PredictLeads is a data provider, not a point-and-click prospecting app, so most teams use it through Clay, a CRM, an automation tool, or their own code.

How to Read a PredictLeads Detection

Four fields carry most of the meaning: first_seen_at shows how long evidence has existed, last_seen_at shows how recently it was observed, source_count shows how many sources agree, and behind_firewall marks evidence from outside the website’s code, such as job descriptions that name internal tools. When a detection stops refreshing, call the technology no longer detected, not removed: a script change, a recrawl gap, or a signature change can each cause the gap.

Technology Switch Events

A technology switch event pairs an incumbent tool that is no longer detected with a direct competitor that is newly detected at the same company. As of October 2026, PredictLeads grades 51,140 switch events by importance: 9,322 high, 30,855 medium, and 10,963 low. Treat each one as a lead to investigate, not a confirmed replacement; a matching shift in job postings is stronger supporting evidence of a possible transition. For the outreach playbook, see competitor displacement with technographic data.

Other Technographic Data Providers Compared

The four providers below are listed alphabetically, not ranked. Each does a specific job well, and each limitation notes where that job differs from a multi-signal technographic workflow.

BuiltWith

BuiltWith is a website technology profiler that crawls sites and records the technologies visible in their code.

• What they offer: website technology lookups, lists of sites using a technology, first and last detected dates, and API access.
• Good for: website-level research, such as sizing the web footprint of an ecommerce platform or an analytics tag.
• Limitation: detection centers on what a website exposes, so internal systems that never appear in page code are harder to see, and hiring, news, and financing signals are not part of the record.
• Bottom line: PredictLeads adds job-description, DNS, and IP-range evidence to website detection and matches it to 133.5M+ company records.

Source: BuiltWith profile and reviews on G2

Coresignal

Coresignal is a public web data provider that sells large company, employee, and job posting datasets.

• What they offer: multi-source company, employee, and job posting records through an API and flat files, with listings on cloud data marketplaces.
• Good for: data teams that want large workforce and job posting datasets to build their own models and signals.
• Limitation: its Datarade profile lists company, employee, and job posting products, with technographics as a category tag rather than a standalone detection dataset, so technology signals have to be derived in-house.
• Bottom line: PredictLeads delivers technology evidence ready to use, with 2B+ active detections that each carry a source and timestamps.

Source: Coresignal data provider profile on Datarade

HG Insights

HG Insights is an enterprise technology intelligence provider that combines technology adoption data with modeled IT spend estimates.

• What they offer: technographic intelligence, IT spend signals, buyer intent, and account analytics, with CRM integrations and enterprise contracts.
• Good for: strategic account planning at large enterprises, where estimated IT spend by product category shapes territory and pipeline decisions.
• Limitation: part of the dataset is modeled rather than observed detection by detection, and contract-based pricing is a heavier commitment for smaller teams and agencies testing a use case.
• Bottom line: PredictLeads exposes observed, source-backed detections on a pay-as-you-go API with a $40 minimum monthly charge.

Source: HG Insights profile and reviews on G2

Wappalyzer

Wappalyzer identifies the technologies on websites through a browser extension, technology lookups, and an API.

• What they offer: a browser extension for on-page checks, lookups by domain, lead lists filtered by technology, and an API for bulk website lookups.
• Good for: quick, developer-friendly checks of a single site and programmatic website lookups.
• Limitation: detection is website-observed, so internal tools named only in job descriptions do not appear, and company event signals sit outside its scope.
• Bottom line: PredictLeads pairs website evidence with behind-the-firewall detection and hiring, news, and financing context in the same API.

Source: Wappalyzer profile and reviews on G2

Technographic Data Provider Feature Comparison

The table scores each provider against the six criteria above. “Not published” means the provider does not document the capability publicly, so treat it as a question for the vendor rather than a no.

Technographic Data for GTM Agencies: What Changes When You Buy for Clients

A GTM agency evaluates technographic data differently from an in-house team, because it sells outcomes built on that data across many client accounts. The question shifts from “is the coverage good?” to “can I deliver this for 10 clients, show each one the evidence, and keep my margin?” Many agencies handle client enrichment inside Clay, where how GTM agencies manage Clay access and credit costs is a live community question. If you are choosing a tech data provider for a GTM agency, four areas decide the fit.

Per-Record Credits Across Many Client Accounts

Seat-based tools charge per user; a metered API charges per record, which maps more cleanly to client billing. PredictLeads meters usage in credits. Company-level endpoints such as /companies/{domain}/technology_detections typically cost 1 credit per response, discovery endpoints typically cost 1 credit per record returned, and the /technologies catalog costs 3 credits per record. Following a company costs 0 credits, and GET /api_subscription reports your monthly limit and usage at 0 credits, so checking burn per client costs nothing.

A worked example: enriching three client lists of 2,000 accounts each with company-level detections comes to roughly 6,000 credits. Pull the technology catalog once and share it across clients rather than per account. Pricing is pay-as-you-go with a $40 minimum monthly charge, the per-credit cost falls as volume rises, and full flat files, webhooks, and historical data carry custom pricing for agencies that need whole-market coverage. Current rates are on the PredictLeads pricing page.

Client Deliverables and Data Rights

Before technographic data goes into a client deck, a CRM you hand over, or a productized offer, confirm three terms in writing with any provider: whether client-facing use is allowed, whether data can stay in a client’s systems after the engagement ends, and whether white-label or resale use needs a separate agreement. These are contract questions, not product features, so settle them before you price a retainer.

Two properties make deliverables easier to defend. Every PredictLeads detection links back to its source, such as a subpage URL, job opening URL, or DNS record, so a client can see why an account made the list. The data is company-level with no personal contact information, and PredictLeads is SOC 2 Type II certified and GDPR and CCPA compliant, which can shorten a client’s security review.

Refresh Cadence and What You Can Promise Clients

Promise clients dated evidence, not a “live tech stack.” PredictLeads crawls high-traffic websites multiple times daily, refreshes job openings about every 36 hours, and, through webhooks set up with its team, pushes new technology detections for followed companies as they appear. Flat-file exports follow scheduled cadences. Write those cadences into your scope, filter deliverables on last_seen_at (for example, detections observed in the last 90 days), and report gaps as “no longer detected” instead of “dropped,” because a missing detection has several possible causes.

Fit With the Agency Stack

Integration effort decides whether a provider gets used across every client account. PredictLeads plugs into the tools agencies already use:

• Clay: a native integration with modules such as Search Company Technologies, so each client table pulls detections using your own API credentials.
• Make and n8n: native PredictLeads modules, including Search Companies Using Technology, for scheduled list builds and CRM updates.
• CRMs: API enrichment writes detections into HubSpot or Salesforce company fields for scoring and routing, as shown in our technographic lead scoring guide.
• Warehouses and reporting: JSONL flat files load into Snowflake or BigQuery for client dashboards.
• AI agents: the MCP server at mcp.predictleads.com lets an agent query detections in plain language (see the MCP integration docs).

PredictLeads customers include Clay, Common Room, FactSet, and Instantly. For most agencies, Clay is the shortest path from a client brief to enriched accounts.

An Agency Workflow for Technographic Client Campaigns

This five-step loop turns a client brief into a monitored target list. Step 2 follows our guide to finding every company using a technology by name.

Why PredictLeads Is the Best Technographic Data Provider

Technographic data earns its place when it changes who you contact and when. Website scanners show what is on a site, and spend models estimate budgets. PredictLeads shows what the evidence says, how recent it is, and what else is happening at the company, across 133.5M+ companies, using public sources only and backed by SOC 2 Type II certification and GDPR and CCPA compliance. To plan an integration, compare API, flat files, webhooks, and MCP delivery or start with the Technology Detections documentation.

Frequently Asked Questions

What is the best technographic data provider in 2026?

PredictLeads is the best overall technographic data provider in 2026 for B2B teams and agencies that need source-backed detections plus company signals. It combines 2,003,496,359 active Technology Detections from five sources with Job Openings, News Events, and Financing Events in one API. Website profilers fit narrower web research, and enterprise spend models fit large-account planning, so match the provider to the job.

What should a GTM agency look for in a technographic data provider?

Look for per-record pricing that maps to client billing, evidence you can show clients, published refresh cadences, and integrations with the tools you already use for client work. Confirm client-facing and white-label rights in writing. PredictLeads meters usage in credits, typically 1 credit per company-level response, attaches a source plus first_seen_at and last_seen_at to every detection, and connects natively to Clay, Make, and n8n.

How much does technographic data cost through an API?

Cost depends on the pricing model: website lookup tools usually sell subscription tiers, enterprise intelligence providers sell contracts, and API-first providers meter usage per record. PredictLeads uses pay-as-you-go credits with a $40 minimum monthly charge, and the per-credit cost decreases as volume increases. Company-level detection lookups typically cost 1 credit per response, and every new account gets 100 free API requests.

Can technographic data detect tools like Salesforce or Snowflake that do not appear on a website?

Yes, if the provider uses more than website code. CRMs and data warehouses rarely leave a script tag, so website-only scanners often miss them. PredictLeads adds job descriptions, DNS records, and IP ranges as sources and flags evidence from outside the website with the behind_firewall field. Treat a job-description mention as evidence of use, planned adoption, or a hiring requirement, not proof of an active deployment.

How often is technographic data updated?

It varies by provider and by source, so ask for published cadences rather than a single “real-time” claim. PredictLeads crawls high-traffic websites multiple times daily, refreshes job openings about every 36 hours, and pushes new detections for followed companies through webhooks. Every detection carries first_seen_at and last_seen_at, so you can filter on recency and report gaps as no longer detected.

Final Thoughts on Technographic Data Providers

The right technographic data provider is the one whose evidence you can explain to a buyer, or a client, in one sentence. Pull detections for 50 accounts you already know, check the sources and dates against what you know, and scale only what holds up. You can test it with 100 free API requests.