salesmatic.ai
Austrian suite of AI applications for sales and planning that plugs into existing ERP, CRM and BI systems. Ten modules cover offer scoring, dynamic pricing, demand forecasting, guided selling, lead scoring and churn prediction, delivered as a managed cloud service.
What is salesmatic.ai?
salesmatic.ai is a suite of artificial intelligence applications specialised in sales and planning, published by QUOMATIC.AI GmbH, an Austrian company based in Traun, Upper Austria. The vendor describes it as an AI advanced sales intelligence suite and positions it deliberately as a layer on top of the software a company already runs: it reads data out of the customer's ERP, CRM and BI systems and, where those systems describe the past, it produces forward-looking scores and forecasts.
The platform provides a shared foundation, dataset management, automation, dashboards for visualisation and editing, and a library of specialised algorithms, on which ten modules are built. Opportunity scoring covers offer optimisation and dynamic pricing. Predictive planning covers sales forecasting, demand prediction and inventory optimisation. The recommender engine covers guided selling and cross- and upselling. The remaining modules address strategic market analysis, lead scoring, lead finding, churn prediction and advanced sales and revenue intelligence. A separate AI strategy consulting service sits alongside the software rather than inside it.
Every module follows the same published sequence: the customer uploads historical data or connects a source system, the platform adds external drivers from the vendor's data warehouse such as sector indices, economic activity and interest rates, an individual model is built per product, product group or country, and the result is delivered in a dashboard whose figures can be exported. Interfaces to Microsoft Dynamics CRM, Salesforce and SAP are announced as already integrated. Delivery is a managed cloud service, and the vendor states that it runs the models itself so the customer does not have to build an internal data science team.
The scientific side is unusually well identified: the chief AI officer is a professor of artificial intelligence at the Hagenberg University of Applied Sciences, and the advisory board is held by the researcher who invented the LSTM architecture at Johannes Kepler University Linz. Named customer references are drawn from the German-speaking market. Performance figures shown on the homepage, ten per cent higher conversion, five per cent higher contribution margins and a threefold time saving, are the vendor's own claims and no supporting study is published. The site is available in English and German only.
What it does
- Score and prioritise open quotations, and propose an optimal customer-specific price for each
- Produce automated sales and demand forecasts, and simulate alternative scenarios
- Optimise inventory, resource, cost and personnel planning from those forecasts
- Recommend cross-selling and upselling products from observed buying behaviour
- Guide buyers step by step on a website, in a shop or through a sales rep application
- Score existing leads and find new companies and contacts matching a market strategy
- Predict customer churn and analyse which markets are worth pursuing
When to use salesmatic.ai / When not to
A quick filter to help you decide if salesmatic.ai is the right fit.
When to use salesmatic.ai
- Mid-sized B2B manufacturers, wholesalers and retailers in the DACH region that already run an ERP, CRM or BI system and hold several years of sales history
- Controlling and finance teams that want rolling, automated forecasts instead of periodic spreadsheet planning cycles
- Sales leaders who need offers scored and prioritised daily, with a suggested customer-specific price for each one
- Demand, supply and inventory planners looking to fold external drivers such as sector indices, interest rates and inflation into their forecasts
- E-commerce and merchandising teams that want guided selling and cross- or upselling recommendations on a webshop, in store or through a sales rep app
When not to use salesmatic.ai
- Anyone hoping to sign up and try the product alone: there is no self-service registration, no free trial and no published price, only a contact form
- Organisations without a usable data history, since every module starts from an upload or a connection to an existing source system
- Teams that need a documented public API, as none is published and no developer or documentation subdomain exists
- Buyers who require published compliance artefacts, because the site carries no privacy policy, no data processing agreement, no subprocessor list and no certification
- Very small companies looking for a low-commitment tool, given that the product is delivered as a consulting-led project with a licence contract
How to use salesmatic.ai
A typical end-to-end flow, from setup to results.
- Request a demonstration or send a message through the contact form, since there is no self-service sign-up
- Agree the scope with the vendor, which delivers the product as a project rather than as a subscription you configure alone
- Upload your historical data, past quotations or sales and order time series, or connect your ERP or CRM to the platform
- Let the platform enrich that data with external sources from the vendor's warehouse, such as sector indices, economic activity and interest rates
- Have the optimal AI model built for your products, product groups or countries
- For the recommender engine, design the recommendation interface first if you do not already have one
- For the recommender engine, work through the cold start phase by creating between 100 and 800 user sessions manually, depending on the project
- Open the dashboard to read daily scores, suggested prices, forecasts and the main influencing factors, and export the figures when needed
- Feed the results back into your sales or planning process so the models keep learning from your corrections and new data
- Download the module whitepapers, which are released against a short contact form, if you need more detail before committing
Pros & Cons
Pros
- Broad functional coverage: ten modules built on one common platform, from quotation scoring to demand forecasting and guided selling
- Pre-built connectors to Microsoft Dynamics CRM, Salesforce and SAP, with the product designed to sit on top of existing ERP, CRM and BI systems
- External drivers such as sector indices, economic activity and interest rates are supplied and maintained by the vendor rather than by the customer
- Operations are handled by the vendor, so no internal data science team is required to keep the models running
- Verifiable scientific backing: the chief AI officer is a professor of artificial intelligence, and the advisory board is held by the inventor of the LSTM architecture
- Named customer references in the German-speaking market, including well-known industrial manufacturers
- European publisher, with the public site hosted in Germany
Cons
- No public pricing whatsoever: no pricing page, no tiers, no order of magnitude, and the shop route on the site returns an empty page
- No free trial and no free plan are announced anywhere
- No privacy policy is published, and the general terms state that the GDPR privacy statement is attached to the contract instead
- No data processing agreement, no subprocessor list and no security certification such as ISO 27001 or SOC 2 is claimed
- Nothing is said about where customer data is hosted or whether it is used to train models
- No public API is documented, and the general terms linked from the legal notice are an Austrian sector-wide template rather than a contract written for this product
- The site is unevenly maintained: placeholder testimonials, a default CMS terms page, a default forum used as an FAQ, an event dated September 2023 still on the homepage and a contact map still pointing at the previous office
Pricing & Plans
No price is published. There is no pricing page, no plan comparison and no figure anywhere on the site; the shop route returns an empty page and the sitemap contains no commercial listing. The company page states only that the solutions are supported and improved through a flexible licensing model, and the general terms linked from the legal notice specify that all prices are quoted in euros excluding VAT, with travel and subsistence charged separately and invoices payable within fourteen days. No free plan and no free trial are mentioned. Pricing is therefore agreed contract by contract after contact with the vendor.
Data, GDPR & hosting
A consolidated view of how salesmatic.ai handles your data.
GDPR overview
The publisher is established in Austria and therefore falls under the GDPR, but the site never claims compliance in so many words. No privacy policy is published: thirteen usual paths were probed and every one returned a genuine 404. The general terms explain why, stating that the privacy statement within the meaning of Articles 13 and 14 GDPR is attached to the contract, and they add only that the supplier binds its staff to Section 6 of the Austrian Data Protection Act. The single compliance page online is a cookie policy, which is the default boilerplate of the underlying CMS. The legal notice carries a Google Analytics disclosure describing transfer of visitor IP addresses to a Google server in the United States. No data protection officer is named and no dedicated privacy address is given.
Who owns the data?
The site publishes no privacy policy, so ownership of customer data is not addressed anywhere in public. The only contractual document linked from the legal notice is the Austrian sector-wide model contract of the WKO trade association for software (UBIT general terms, 2024 edition), not a document written for this product. Under those terms the customer receives a non-exclusive, non-transferable, non-sublicensable and unlimited right of use, while copyright in the software remains with the supplier. Both parties owe mutual confidentiality over business secrets, and subcontractors tied to the supplier are expressly not treated as third parties. Nothing states who owns the customer data itself, nor what the vendor may do with it.
Reuse rights
The product pages describe the data flow clearly, but the contract does not. Customers upload their own historical records, past quotations, order and sales time series, or connect their ERP or CRM directly. salesmatic.ai then enriches that material with external sources drawn from the vendor's own data warehouse, such as sector indices, economic activity and interest rates, and builds an individual model per product, product group or country. A feedback loop feeds new data and user corrections back into the models so that forecasts improve over time. Forecasts can be exported at any time, and the recommender module returns behavioural insights on conversion, abandonment and profiling. Whether the vendor may reuse customer data beyond the customer's own models is never addressed: the general terms state only that the privacy statement required by Articles 13 and 14 GDPR is attached to the individual contract, and it is therefore not public.
Data retention & training
Hosting summary
The site says nothing about where customer data is processed or stored. There is no privacy policy, no data processing agreement and no trust or security page, and the general terms state that the GDPR privacy statement is attached to the individual contract rather than published. The only measurable element concerns the public website, not the platform: it resolves to a single address operated by Oracle Corporation in Frankfurt am Main, Germany, on real hosting infrastructure rather than a content delivery network. Oracle also appears in the vendor's partner banner, which makes that choice consistent but still says nothing about where models are trained or customer records are kept. Since the publisher is established in Austria, European law applies to the relationship, but the specific jurisdiction of the processing has to be obtained from the vendor directly.
Things to keep in mind
Risks and trade-offs to weigh before adopting salesmatic.ai.
- Data terms are invisible before signature: with no privacy policy, no processing agreement and no subprocessor list published, everything about how your sales history is handled has to be negotiated in writing rather than read beforehand
- The vendor never states whether customer data is used to train models, and never says where the platform hosts it, so both questions must be asked explicitly
- Forecasts and scores presented as objective can quietly replace commercial judgement; the vendor itself frames the product as a complement to people, and that framing only holds if the team keeps challenging the output
- Dynamic pricing suggestions can drift towards outcomes nobody can explain to a customer, and the site publishes nothing about how a suggested price is justified
- The performance figures on the homepage, ten per cent more conversion, five per cent higher margins, a threefold time saving and an eightfold return, are vendor claims with no published study behind them; treating them as a forecast for your own case would be a mistake
- Once forecasting and pricing run on the vendor's models and its external data warehouse, moving away means rebuilding both, and the operating model deliberately avoids you having internal data science capacity
- Several pages still carry unedited template content, including placeholder testimonials and default CMS terms; check that any document you are shown was written for this product before relying on it
Setup & Integrations
Technical difficulty
Setup is a project, not a sign-up. There is no self-service registration; scope is agreed with the vendor first. The customer must supply a usable data history and either upload it or connect a source system, and under the general terms provides documents, test data and test facilities at its own cost. The vendor claims a click-and-configure approach and faster delivery than internal development. The recommender module is the heaviest: it may require a user interface to be designed and a cold start phase of 100 to 800 manually created sessions. Day-to-day operation is handled by the vendor.
Deployment
Integrations
Supported languages
Behind salesmatic.ai
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
Who publishes salesmatic.ai?
How much does salesmatic.ai cost?
Is there a free trial or a free plan?
How do you get started?
Which systems does it integrate with?
Is there a public API?
Is there a mobile app?
Which interface languages are available?
Where is customer data hosted?
Is the product GDPR compliant?
Should you pick salesmatic.ai?
salesmatic.ai is a serious, narrowly focused product from an established publisher. The company behind it has been on the Austrian commercial register since 2017, its domain has been live since 2018, and the scientific credentials of its leadership are unusually easy to verify. The functional scope is genuinely broad: ten modules built on one platform, covering the whole chain from scoring an individual quotation to forecasting demand and guiding a buyer through a catalogue, with connectors to the ERP and CRM systems most mid-sized industrial companies already run.
What is missing is commercial transparency. No price is published, no trial exists, and the only way in is a contact form. More importantly for a tool that ingests a company's entire sales history, nothing is published about data handling: no privacy policy, no processing agreement, no subprocessor list, no hosting location and no statement on whether customer data is used for training. The general terms linked from the legal notice are the Austrian trade association's sector-wide template rather than a contract drafted for this product, so they describe an industry norm rather than a commitment specific to salesmatic.ai.
The site itself is unevenly maintained, with placeholder testimonials, default CMS pages used as terms and FAQ, an event from 2023 still on the homepage and a contact map still showing the previous office. None of this undermines the product, but it does say something about how the shop window is kept.
This is a tool for a company that is looking for a project partner and is prepared to negotiate scope, price and data terms in writing. Anyone hoping to evaluate an AI sales platform on their own, over a weekend, will not be able to do so here.
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