https://redbumerang.com/en/ Industrial lead generation and industrial process AI for manufacturers across Europe and the United States. en https://redbumerang.com/en/ https://redbumerang.com/en/ Industrial lead generation and industrial process AI for manufacturers across Europe and the United States. Thu, 03 Sep 2026 00:00:00 GMT Industrial lead generation and industrial process AI for manufacturers across Europe and the United States. Source: https://redbumerang.com/en/ ## Industrial lead generation. Industrial process AI. We bring order to industrial processes, then automate them: outward into the market to build your sales pipeline, and inward into operations to rebuild how the work gets done. Book a 30-minute meeting See what we do **Work across** - Manufacturing·Machinery·Automotive·Chemicals·Energy·Construction·Logistics·Telecom·Aviation·Insurance·Food & beverage·Contact centres·Applied research - Slovenia·Croatia·Poland·Germany·Switzerland·Netherlands·United Kingdom·Sweden·United States **What we do** ## We fill your pipeline. We rebuild your processes. Two verticals, one method — and both start in the same place: mapping the work as it actually runs. Vertical 01 — Industrial lead generation ### From market to a qualified sales pipeline We run your entire outreach pipeline: target companies, decision makers, channels, campaigns and qualification. You close. Global reach 69 countries Multi-channel approach LinkedIn · Email · Phone Managed outbound Run by us - **400–1,000** — Monthly activities per salesperson - **4–12** — Decision makers mapped per company - **100+** — Industries tested in campaigns Learn more → Vertical 02 — Industrial process AI ### From undocumented processes to an AI production system A business process nobody has written down cannot be automated, only guessed at. We map how the process actually runs, put AI where it earns its place and connect the systems that were never meant to connect. Process mapping As it actually runs Closed-system integration Reverse engineered Model options Frontier or private, air-gapped models 1 month→ - **4–8 h** — Campaign preparation 4 / month→ - **2 / day** — Clients onboarded **Metrics from our own automated lead generation process.** Learn more → **Track record** ## Everything here is already running. Five years of production work across both verticals. Six systems are live and six thousand campaigns run each year. None of it is a pilot. Lead generation · every year - **6,000+** — Campaigns run - **2M+** — Decision makers reached - **360** — Clients since 2020 - **69** — Countries covered Systems in production · not pilots ### Market intelligence platform One classified base covers roughly 1.9 million industrial companies across 69 countries and gives us a current view of the market. ### Solar prospecting at national scale Every industrial plant in a country scored for suitability from desk data — roughly 30,000 of them, without a site visit. ### Managed lead generation engine From market definition to a qualified list of opportunities with verified decision makers — up to 18 countries in a single sweep. ### Order system rebuilt from one spreadsheet 78 undocumented sheets turned into a production application with roles, rules and an audit trail, delivered in days. ### Sales support across closed systems From enquiry to quote and optical route: three closed systems connected, two of them reverse engineered. ### Call quality at full coverage 16,005 calls and 434 hours of recordings reviewed overnight, unsupervised, instead of sampling a handful. **01 / 02** **01** **02** **03** **04** **05** **06** 5 AI steps 3 AI steps 4 AI steps AI as the build engine 2 unlocked sources 6 AI steps **Integrations** ## We connect to what you already run. Your ERP, your CRM, the spreadsheet nobody documented, the national data service with no export button. Nothing gets replaced. Systems you already run ERP CRM Order systems Legacy spreadsheets PDF · Excel · Word Data we bring Firmographic registers National geodata Satellite imagery Trade press & statistics The layer between Red Bumerang Mapped Connected Automated What comes back Ranked target lists Internal web application Generated documents Excel export Monthly reports Channels we run LinkedIn Email Phone Two of the sources in our production systems had no API at all. We reverse-engineered them. This is normal in industry, not the exception. Where policy requires it, the whole system runs inside your own environment. **05** **04** **05** **03** **Next step** ## Bring us one process or one market. Thirty minutes, no deck. Bring a process and we map where the order is missing and where automation earns its place. Bring a market and we size it — how many companies are really in it, and who decides. Either way you leave with a number and a first step. Book a 30-minute meeting or write to info@redbumerang.com ]]> https://redbumerang.com/en/lead-generation/ https://redbumerang.com/en/lead-generation/ Red Bumerang runs industrial outreach: market classification, decision-maker mapping, multi-channel campaigns, qualification and booked meetings. Thu, 03 Sep 2026 00:00:00 GMT Red Bumerang runs industrial outreach: market classification, decision-maker mapping, multi-channel campaigns, qualification and booked meetings. Source: https://redbumerang.com/en/lead-generation/ Outward / managed pipeline **Red Bumerang/Verticals/Outward** ## Managed lead generation. We run your entire outreach pipeline: target companies, decision makers, channels, campaigns and qualification. Your team closes. Book a 30-minute meeting See what we run - **400–1,000** — Monthly personalised sales activities per salesperson - **4–12** — Verified decision makers mapped per company - **100+** — Industries tested in live campaigns - **69** — Countries in our classified company base **Order first** ## A market you haven’t classified isn’t a market. It’s a list. Most outreach is already lost before the first message is written, because the target set was whatever was to hand — a directory export, a trade-fair badge scan, a CRM nobody has pruned since 2019. Volume cannot fix a wrong list; it only spends your name faster. So we start where the order is missing: which companies are genuinely in this market, what they actually make, who inside them decides, and which of them are buying this quarter. Roughly 1.9 million industrial companies across 69 countries, classified — then narrowed to the few thousand that are yours. Only then does automation earn its place. ## The list is not the preparation. It is the campaign. Begins withClassifying the market Never begins withBuying a contact list **Market cycle** ## Demand relocates. It does not disappear. German automotive is cooling, and its Central European supply base with it, while machinery, packaging and energy are growing two countries to the east. The plant still needs the machine; the order has simply followed the capacity. A target set inherited from last year does not represent a smaller opportunity. It represents the wrong one. Before anything is written, we re-read the map: which industries in which countries are buying this quarter. Pause **Reading now** German automotive is in contraction, dragging its Central European supply base with it. **Strongest this quarter** **Weakest this quarter** **Contracting** **Expanding** Index −100 to +100 Illustrative surface · the shape of the read, not a published index ### What moves The budget, not the need. A cooling market rarely means demand has disappeared. Spending has shifted to the country that gained the volume. ### What we re-read Industry, country, quarter. The target set is rebuilt each cycle rather than inherited, so the campaign follows the money instead of the org chart. ### What it changes Which two thousand companies get the campaign — and, more usefully, which twenty thousand do not. **Full-cycle delivery** ## Everything in managed lead generation. There is no new tool to log into or dashboard to learn. We run the pipeline end to end and leave your team to do the one thing it is paid to do: have the conversation. ### Target identification Companies identified and scored against your customer criteria, drawn from a classified base of roughly 1.9 million industrial companies across 69 countries. ### Decision maker mapping We map 4–12 verified decision makers per company, with email, LinkedIn and phone details checked before anything is sent. We do not rely on one generic address. ### Multi-channel outreach LinkedIn, email, phone and the niche platforms that matter in your industry. The mix is chosen for each market, not imposed by a template. ### Personalised campaigns 400 to 1,000 personalised activities a month per salesperson, with variants running side by side to show which copy works. ### Lead qualification Hot-lead triage, AI-assisted scoring and the qualification conversation itself, so your team sees only genuine opportunities. ### Meeting booking A full briefing pack for every qualified meeting: the account, the contact, the history and the reason for the reply. Your team walks in prepared. **01** **02** **03** **04** **05** **06** Market classification Verified contacts A/B tested AI-assisted scoring Briefing pack included LinkedIn · Email · Phone **Getting started** ## It starts with one hour. Before a single message goes out, we sit down with you and document your sales process properly, in your words. Seven questions. Most companies have never written down an answer to the fourth, and it is usually the one that makes the campaign work. Seven questions / one market definition 01What your sales process actually looks like today 02What you sell and your commercial goal for this year 03Why your customers buy from you 04Why prospects do not buy from you 05Who in the company really makes the purchase decision 06Which countries and business activities you want to target 07Which roles to approach — procurement, technical and sales roles, or board members **Then we build · who we contact** ### The target base Companies and named decision makers, scored against the criteria we have just agreed. You see the list before it is used. **Then we build · what we say** ### The approach The messages you will actually send, written in your voice, backed by your evidence and reviewed by you before the first one goes out. **Then we build · how we know** ### The test Variants run against each other from week one. We have tested messages in more than 100 industries, but we never assume which one will win. **The channel** ## Industrial companies still treat LinkedIn as a noticeboard. That is the opening. Most industrial B2B companies use LinkedIn to post and wait. We use it to prospect: named people at named companies, each with a specific reason to reply. We pair it with email, phone and niche platforms so decision makers are reached on the channels they actually answer. Personalisation means the real name, company and role, with a genuine reason to make contact. It does not mean a merge field. Personalisation isA reason to reply Personalisation is notA merge field ●Systematic prospecting removes the feast-and-famine cycle. A pipeline built in the quarter you need it is already too late; the work runs every month whether or not the last one closed. ●Relevance outperforms volume. A message that names the person, the company and the reason is more likely to be answered. Without them, the market learns to ignore you. ●Multi-channel finds people where they respond. A technical director who never opens LinkedIn takes a call; a procurement lead who never takes calls replies to email. The mix is chosen per market. ●A/B testing settles the copy with evidence. Across more than 100 industries the winning message has rarely been the one the room expected. **Track record** ## This has been running for five years. Lead generation is the older of the two verticals and the foundation for everything else. Every figure below is production volume, not a pilot. - **6,000+** — Campaigns run per year - **2M+** — Decision makers reached per year - **360** — Clients since October 2020 - **~1.9M** — Companies classified across 69 countries - Manufacturing·Machinery·Automotive·Chemicals·Energy·Construction·Logistics·Telecom·Aviation·Insurance·Food & beverage·Contact centres·Applied research - Slovenia·Croatia·Poland·Germany·Switzerland·Netherlands·United Kingdom·Sweden·United States **Next step** ## Bring us one market. Thirty minutes, no deck. Name the market you want and we size it on the call: how many companies are genuinely in it, how many decision makers that represents and what a first campaign would cover. You leave with a number and a first step, even if we do not work together. Book a 30-minute meeting or write to info@redbumerang.com ]]> https://redbumerang.com/en/process-ai/ https://redbumerang.com/en/process-ai/ Red Bumerang maps industrial processes as they run, applies AI where it earns its place and connects the result to your existing ERP, CRM and data. Thu, 03 Sep 2026 00:00:00 GMT Red Bumerang maps industrial processes as they run, applies AI where it earns its place and connects the result to your existing ERP, CRM and data. Source: https://redbumerang.com/en/process-ai/ Inward / production systems **Red Bumerang/Verticals/Inward** ## Industrial process AI. A process nobody has written down cannot be automated, only guessed at. We map how the work actually runs, put AI where it earns its place, and connect the systems that were never meant to connect. Book a 30-minute meeting See what a build looks like - **~2 min** — To draft a customer proposal, down from as much as a month - **~30,000** — Industrial plants scored for suitability, with zero site visits - **78 → 1** — Undocumented sheets rebuilt as one production application - **16,005** — Calls reviewed overnight, with full coverage rather than a sample **Order first** ## Nobody has written this process down. That is the project. Ask three people how a process runs and you get a diagram from 2019, a colleague who simply knows, and a workbook with seventy-eight tabs: three conflicting accounts, none of which reflects how the work actually runs. This is why industrial AI fails: the model is pointed at a description rather than the operation. So we begin by reading the work itself: what moves, who really decides and which system nobody can export from. That map is a deliverable in its own right, before any model is chosen. Only then does automation have a process it can reliably follow. ## We do not automate the process you describe. We automate the one that runs. Begins withReading the work Never begins withThe diagram on the wall **The shape of a build** ## One feed. Two processes. Two outputs. Every system we put into production has the same skeleton. Your data enters once — from the ERP, or from whatever has been standing in for one — and drives the processes that used to be done by hand. Both write into a single source of truth, so the record and the reasoning behind it live in one place and can be audited afterwards. Two things come out: an internal application your team works in daily, and documents that are generated rather than typed. And every run feeds the next one. **Process schematic** - Source data - Automated step - Step with AI - Source of truth 1 feed 2 processes 2 AI steps 2 outputs Schematic · step labels stand in for your own ### Why one feed Re-entry is where the truth splits. The moment the same figure is typed twice, two versions of it exist and somebody spends their week reconciling them. ### Why one source of truth An answer nobody can trace is not an answer. Records and the context behind them sit together, so a decision can be explained months later. ### Why two outputs People need a place to work; the business needs paper. One application your team uses every day, and the documents that used to be typed one at a time. **Where AI earns its place** ## The question is never whether to use a model. It is which step deserves one. Most of a working system is ordinary code. Put a model where a rule belongs and the project becomes unpredictable, expensive and difficult to audit. Put a rule where judgment belongs and the automation may be switched off by month three. Four tests guide the decision. **Test 01** ### Repeated judgment → the model Reading a document, scoring a plant for suitability, deciding whether a call went the way it should have. It is the kind of work someone repeats a thousand times in much the same way but has never been able to document. **Test 02** ### Exact rules → code A discount table, an approval threshold, a tax rule. If it can be written down precisely, a model adds only another way for it to go wrong. **Test 03** ### No export button → reverse engineering Two of the sources in our production systems had no API at all. In industry that is the normal case, not the exception, and it is usually the reason the process was still manual. **Test 04** ### Policy says no cloud → your environment Frontier models where they are permitted, a private deployment inside your own infrastructure where they are not. The decision is made per system, not once per company. **In production** ## Two systems, described without naming anyone. Client work is covered by non-disclosure, so the companies remain anonymous and the numbers provide the evidence. Both systems are running today; neither was a pilot. **Case 01 · Order handling** ### Seventy-eight sheets, no owner, no specification The workbook ran the order process. Nobody had written down how. Every rule lived inside a formula, every exception in somebody’s memory, and the file could no longer be edited safely by more than one person at a time. We read it end to end, recovered the rules rather than guessing them, and rebuilt it as a production application with roles, permissions and an audit trail in days rather than quarters. **Spreadsheet to system** - Legacy workbook - Rebuilt in production 78 sheets read Rules recovered, not guessed Production in days ### What was read The whole file, not a sample. Seventy-eight sheets, every formula and every cross-reference, including the tabs nobody had opened in two years. ### What was recovered The rules, stated explicitly. This included several the business did not know it was applying, and two it no longer agreed with. ### What was delivered An application, not a spreadsheet with a nicer front end. Roles, permissions, an audit trail, and more than one person able to work at once. **Case 02 · Call quality** ### Every call reviewed, not a sample Quality assurance in a contact centre normally means a supervisor listening to a handful of calls a week and extrapolating from them. We processed 16,005 calls and 434 hours of recordings overnight without supervision, flagging them by category: where the script broke and where no next step was agreed. Coverage increased from a sample to every call, leaving supervisors more time to coach the people identified by the flags. **Call quality · 100% coverage** - Reviewed audio - Flagged segment 100% of calls, not a sample Flags by category No supervisor review time ### What changed in coverage From a handful a week to all of them. A sample can show overall patterns; it cannot identify which call lost an account. ### What changed in speed 434 hours of audio, reviewed overnight. The flags are on the supervisor’s desk before the shift starts, not three weeks later. ### What changed for the team The supervisor spent less time listening and more time coaching. The scarce resource was never the audio. It was the attention. **Three more, in short** **A national telecom operator** - Up to 1 month→ Drafting a customer proposal. The whole sales team now uses it daily. **An EU energy optimisation group** - **~2 minutes** — A site visit each→ Every industrial plant in a country scored for suitability from desk data, without a site visit. **Red Bumerang · our own operation** - **~30,000 scored** — 1 month→ Campaign preparation. Client onboarding went from four a month to two a day. We ran it on ourselves first. - **4–8 hours** **Where it runs** ## Nothing gets replaced. The system attaches to what you already run: the ERP, the CRM, the spreadsheet nobody documented, the national data service with no export button. Deployment is decided system by system, according to your policy. **Models** Frontier models where they are permitted, or a private deployment inside your own environment where they are not **Inference** Run on our infrastructure or yours; where your policy requires it, nothing is routed through a third-party AI cloud **Languages** Speech and text systems work directly in Slovenian, Croatian, Latvian, Lithuanian, Estonian and Hungarian; they are trained for each language rather than translated **Sources with no API** Reverse engineered — two of the sources in our production systems had none at all **Data residency** Stays wherever your policy requires it to stay — including entirely inside your own network **Handover** Your team uses the application daily; we continue to support and improve it after go-live **Processes we have rebuilt run in** - Manufacturing·Telecom·Energy·Construction·Contact centres·Food & beverage·Logistics·Applied research **Next step** ## Bring us one process. Thirty minutes, no deck. Bring the one that eats a week every month, or the one only a single person knows how to run. We map where the order is missing, which step, if any, deserves a model and what the first version would cover. You leave with a clear outline and a first step, even if we do not work together. Book a 30-minute meeting or write to info@redbumerang.com ]]> https://redbumerang.com/en/company/ https://redbumerang.com/en/company/ Red Bumerang is a Ljubljana-based industrial lead generation and process AI company, with 360 clients since October 2020 and six systems in production. Thu, 03 Sep 2026 00:00:00 GMT Red Bumerang is a Ljubljana-based industrial lead generation and process AI company, with 360 clients since October 2020 and six systems in production. Source: https://redbumerang.com/en/company/ **Red Bumerang/Company** ## We built it for ourselves first. Red Bumerang began as a LinkedIn outreach agency in Ljubljana, running campaigns for manufacturing companies one at a time, by hand. We solved every bottleneck in our own operation before offering the solution to anyone else. Book a 30-minute meeting How we got here - **360** — Clients, cumulative since October 2020 - **~1.9M** — Companies classified across 69 countries - **6** — Systems running in production, none of them pilots - **100+** — Industries tested in live campaigns **What we are for** ## To make industrial AI something mid-size manufacturers can put into production. Not a research project, not a pilot that quietly ends after the budget does. Industrial AI has a credibility problem because too much of it is sold before the work it is meant to automate has been written down. We do it the other way round: order first, then automation — outward into a market to build a pipeline, or inward into an operation to rebuild how the work runs. Two directions, one discipline. **The path here** ## Every tool started as our own bottleneck. Nothing on this site was invented in a workshop and then sold. Each part exists because our own operation hit a bottleneck and we had to build a way through it. ### One campaign at a time, by hand At first, we were an outreach agency in Ljubljana, running lead generation for manufacturing companies. We assembled lists manually, wrote messages one by one and read the results from a spreadsheet. It worked, but did not scale beyond a certain number of clients. ### The same four bottlenecks kept appearing Bad data. Decision makers nobody could reach. Manual work that could not scale. Outreach that sounded generic in a market that punishes it. Every manufacturing sales team knows this list. We experienced these problems as operators, not as outside consultants. ### So we built what we needed, and used it first A classified base of roughly 1.9 million industrial companies across 69 countries. Outreach automation. Voice. Internal applications built where a spreadsheet had been standing in for a system. Private infrastructure for work that cannot leave a client’s network. Each one solved a problem in our own operation before a client ever saw it. ### Then the same discipline turned inward Mapping a market and mapping an operation are the same discipline: find the order that nobody has written down, then automate what remains. That is why one company can do both industrial lead generation and industrial process AI without becoming two. **01** **02** **03** **04** **Client zero** ## The honest test of a system is whether you run your own business on it. We do. These two numbers are not from a client engagement; they show what happened to Red Bumerang’s own operation when we applied the method to ourselves. They also explain why we are willing to quote timelines that can sound implausible. **Preparing a campaign** - 1 month→ From market definition to a campaign ready to send. The work did not get smaller; the parts that never needed a person stopped needing one. **Onboarding a client** - **4–8 hours** — 4 a month→ The one-hour onboarding conversation stayed unchanged. Everything around it, including the target base, the approach and the first test, stopped being assembled by hand. - **2 a day** **What we stand for** ## A commercial team with an operator’s discipline. Four commitments. They are short because they are meant to be checkable, not admired. **01 · Precision** ### Better targeting, not more noise The point of classifying a market is to decide who not to contact. A campaign that reaches everybody has not been aimed at anybody. **02 · Transparency** ### We show the process, the numbers and the tools You see the target list before it is used and the messages before they go out. If a figure on this site is unverified, we say so rather than present an estimate as fact. **03 · Domain first** ### Industry knowledge comes before the model A model without the rules behind quote approval may produce something that reads well but cannot be used. We start with the domain, every time. **04 · Partnership** ### We stay with the system after go-live Systems often falter at handover. Your team uses the system daily; we keep it running and continue to improve it with them. **Where we are** ## Built in Ljubljana. Working across Europe and the US. One office, one team, and clients in nine countries on two continents. Everything described on this site is delivered from here. **The office** **Company** Red Bumerang d.o.o. **Address** Trg komandanta Staneta 8 SI-1000 Ljubljana Slovenia **VAT ID** SI46075143 **Reg. no.** **Reach us directly** **Phone** **Email** info@redbumerang.com **LinkedIn** Red Bumerang **Clients in** - Slovenia·Croatia·Poland·Germany·Switzerland·Netherlands·United Kingdom·Sweden·United States 7260059000 +386 51 624 925 Director Register **Contact** ## Write to us. If a call is the wrong first step, send the question instead. Tell us which market you are trying to reach or which process costs you a week each month, and you will get a considered answer rather than a brochure. **Send a message** Your name * Company * Work email * What is this about A market — lead generation A process — process AI Both, or not sure yet Something else Your message * I agree that Red Bumerang may store and use these details to answer my enquiry, as described in the Privacy Policy. Send the message **What happens next** No sequence, no drip campaign. A person reads it and answers it. We run outreach for a living, so we know what it feels like at the other end. - 01You get a reply within one working day, written by someone who read your message, not pulled from a template. - 02If the answer is short, it stays an email. Not everything needs a meeting, and we will say so. - 03If it is worth thirty minutes, we propose a time and come to the call with the numbers for your market or process. Prefer the phone? +386 51 624 925. Or write straight to info@redbumerang.com. Reply within one working day **Next step** ## Thirty minutes, no deck. Bring a market and we size it on the call: how many companies are genuinely in it and who decides. Bring a process and we map where the order is missing and which step, if any, deserves a model. You leave with a number and a first step, even if we do not work together. Book a 30-minute meeting or write to info@redbumerang.com ]]>