Analytics Legends — SAP Analytics Intelligence

Search the published Analytics Legends directory of SAP AI & analytics service providers — placement agencies, Big-4 and ESN practices, SAP vendors, platforms and community groups — by country, region (EMEA · AMER · LATAM · APAC · AFRICA), kind, declared SAP module and free text. Returns name, HQ country/city, website, careers URL and a one-line editorial claim. SAP END-CUSTOMER companies are NOT

Answer a COUNTING question about the published firm directory in one call: how many organisations per country, per REGION (the six-value geography), per kind, per declared SAP module, or per SAP signal band — with the same `country`/`kind`/`module`/`query` filters `search_firms` takes, so you can count a slice as easily as the whole. Use this instead of paging `search_firms` and tallying rows: the

Fetch one organisation from the published directory by its database slug (`rows[].slug` from search_firms, verbatim). Returns the same public fields plus `partnerships_declared`, the count of partnerships this directory records for the firm — 0 on ~77 % of rows (re-measured 2026-09-30 on the published tranche: 77,1 %; it read ~97 % until the 2026-09-30 brand-family pass derived 3 730 sibling links

Breakdown of the published firm directory by organisation kind, with a live row count per kind. Use this before search_firms to know what the population actually is instead of guessing.

The subset of the published directory where a consultant can CREATE A PROFILE — freelance marketplaces, job boards with candidate profiles, talent platforms and expert networks — each with its signup URL, an editorial confidence grade and the date it was assessed. This answers the entering-contractor's first practical question ('where do I register?') in one call. Everything here is also in search

Search every SAP contract and permanent-role posting Analytics Legends publishes to an ANONYMOUS visitor. Only the SITE RADAR leg below is the population a human browses on /opportunities/, where each of its postings has its own prerendered page; the PROMOTED leg is served to agents only — it is not listed on /opportunities/ and its rows have no page of their own (citation_scope "section_hub"). It

Search the Analytics Legends market-news corpus. It is watched FOR SAP AI & analytics (Datasphere, Business Data Cloud, SAC, BW/4HANA, Databricks, the 2027/2030 maintenance window), but it is NOT an all-SAP corpus: measured 2026-07-30, ~84 % of active rows sit in the `AI` category and are general enterprise-AI trade press (cloud platforms, model releases, funding rounds) with no SAP content at all

Search the SAP AI & analytics concept encyclopaedia — the vocabulary of the stack, written for practitioners. Returns slug, title, category, level, tags and the editor's summary. `level` is GRADED on every active row since 2026-09-18 (the CHECK constraint accepted only the legacy vocabulary OR NULL, so the loader wrote NULL rather than fail; 108 of 330 were blank). A null, if one ever returns, mea

Fetch one concept entry by slug: title, category, level, tags and the editor's summary. Written by a named human editor, not generated. `level` is GRADED on every active row since 2026-09-18 (the CHECK constraint accepted only the legacy vocabulary OR NULL, so the loader wrote NULL rather than fail; 108 of 330 were blank). A null, if one ever returns, means 'not graded', never 'Beginner'. The card

List the Analytics Legends deep-research studies with their edition, as-of date, audience, word count and canonical URL. METADATA ONLY: study bodies are a paid Consultant-tier deliverable, served by `get_study` on this same endpoint with a subscriber key. Use this to tell a reader that a study exists and where to read it. ONE ROW IS ONE LANGUAGE EDITION, NOT ONE STUDY: each study is published in e

The PUBLIC day-rate aggregate for SAP AI & analytics freelance work: min/max daily rate by country, specialisation and seniority — `daily_rate_min` / `daily_rate_max` (plus `daily_rate_median`, `daily_rate_p10`, `daily_rate_p90` when the source publishes them), every amount in the row's own `currency` — with source, source date, confidence and the sample the source states. This is the free aggrega

The canonical SAP module/product taxonomy Analytics Legends classifies against (codes and EN/FR labels by category). Use it to normalise a user's loose product wording — 'SAC', 'Analytics Cloud', 'Datasphere' — onto the codes the other tools filter on.

Search the Analytics Legends Academy — the written training modules on SAP Datasphere, Business Data Cloud, SAP Analytics Cloud, BW/4HANA and Databricks — by track, level and free text. `_meta.tranche_total_row_count` carries the live catalogue size on every call; it is the only count to quote. Returns the catalogue entry: id, slug, EN/FR title, track, level, duration in minutes, tags and the edit

The RELATIONS between the platform's teaching objects — which Academy module teaches which concept, which study covers which module, what a concept relates to. THIS IS THE ONLY TOOL ON THIS SERVER THAT SERVES EDGES; the others serve rows. Ask it what connects to what, not what exists. SCOPE, AND IT IS NARROWER THAN 'the knowledge graph': it carries four node types — `concept`, `module`, `study`, `

The FULL encyclopaedia card for one concept — body, cheat sheet, glossary, pro tip, and the four analysis tables (decision table, peer comparison, named pitfalls, performance facts), EN, FR and DE, plus why-it-matters and key points (those two are also published free on the concept page; here they come structured, in three languages, in the same payload) — the corpus the €29.90 Consultant Pass sel

Read one Analytics Legends study BODY — the paid text behind list_studies' metadata. Requires a subscriber API key, Consultant tier or above. Bodies run to 38k words and exceed the 256 KiB response ceiling, so this tool serves STRUCTURE first: called without `section` it returns the section list and the introduction; pass `section` (a heading from that list, matched case-insensitively) to read one

Read one Academy training module in full — body, learning objectives and summary, EN, FR and DE — the written course corpus the €29.90 Consultant Pass sells. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same ti

Search the SAP END-CUSTOMER corpus — the companies that RUN SAP, not the firms that sell services (those are search_firms). This is the paid Legend+ dataset locked away from the public surface on 2026-07-08; it requires a subscriber API key, Legend tier or above. Verification status is SERVED, never silently filtered: `sap_client_verification_status` and `status` are columns on every row ('verifie

The full profile of one SAP end-customer — SAP footprint (products in use, modules known), analytics solutions, identity and evidence fields. Requires a subscriber API key, Legend tier or above. `id` comes verbatim from find_sap_clients.rows[].id.

The one-call brief a services practice reads before opening a subsidiary in another region: providers already there (by kind and by country, and how many are LOCAL entities versus members of multi-region groups), SAP end-customers there (by country and by industry — counts from the Legend corpus, never rows), live opportunities by country, and the BRIDGE GROUPS — brand families that hold entities

Rank the LOCAL service providers of a target country or region — the firms a practice partners with, subcontracts to, or acquires to enter a market. `local_only` (default true) keeps firms with NO sister entity in another country (read from the brand-family key of the SSOT): a subsidiary of a global group is a competitor, not a partner. Filter by kind and by DECLARED SAP module; rows carry the dec

The paid intelligence profile of a services firm — SAP practice size and partner level, delivery flags per product, typical day rate and seniority, notable clients, analytics practice summary, and a LinkedIn company URL (present on ~71% of the corpus, re-measured 2026-09-05 on 9,104 profiles — it read ~39% from 2026-08-10 to 2026-09-05, i.e. a third of the corpus below the truth, because an enrich