Use cases with no euro behind them
The list from the workshop has 60 entries, none of them an annual figure finance would sign off
Time saved and cost reduced get mixed up, and the steering committee notices
Your AI use cases. Priced in euros.
We break your search fields down into processes, put a euro figure on every AI use case and tell you whether to build it or go with a partner.
Starting point
Everyone has an AI use case list. Almost nobody has a basis for deciding.
80 % known, 20 % overlooked
Chatbot, document search and meeting notes are well covered
The leverage in procurement, treasury and pricing sits across departments, physical AI is missing entirely
Make or buy by gut feeling
IT wants to build, the business wants to buy, the vendor promises everything
Whether you go live in six or in eighteen months hangs on that one question
Pilots that stay pilots
The churn model runs in one country, the negotiation bot only for small orders
The leverage sits in the rollout, and only people who know the processes can see it
Sound familiar? Tell us where your use cases get stuck.
Start with your search fields
We break your search fields down into real processes and deliver the AI use cases that pay off.
You bring the fields where you suspect AI potential and the goals that count: cost, revenue, risk. We map the processes behind them, score them on P&L hardness, evidence and scalability and derive use cases from that. Each one gets an estimated annual value and a route to implementation. The AI engine behind it is called Tautiom.
Here is what you get:
Result
This is what lands on the table.
A map of your use cases with annual value and route to implementation, behind it the processes and the derivation.
Use case map
- Bundling and renegotiation analysisProcurement, cost≈ 3 m€ / yearMake
- Supplier search, wider bidding fieldProcurement, cost≈ 3 m€ / yearPartner
- Autonomous negotiation for standard demandProcurement, cost≈ 1.5 m€ / yearScale the pilot
- Group-wide churn early warningKey accounts, revenue≈ 900 k€ / yearScale the pilot
- AI cash flow forecastTreasury, interest≈ 750 k€ / yearMake
Example figures. In the sprint we calculate on your baseline.
Map the processes
First we look at how the work in your search fields actually runs today.
Search field 1 of 5, indirect procurement, 8 processes
- 1.01 Category and spend analysisData scattered, hypotheses built by hand across several tools5.0
- 1.02 Supplier searchSearch tools are prototypes, the search stays buyer-driven4.6
- 1.04 Selection and negotiationAutomation only for the long tail, the rest manual4.9
- 1.05 Purchase to payGoods receipt and non-PO invoices by hand3.1
Process breakdown
Around 40 processes, each with friction and a score
Every search field is broken into its processes: what happens, who does it, which systems, where it snags. Interviews, documents and Tautiom research produce a longlist that internal lists usually do not have.
Baseline, 1.01 category and spend analysis
4×Frequency per year
40 hEffort per run
2People
60 %automatable
- Estimated baseline
- ≈ 160 hours and ≈ 14.4 k€ effort per year, 7 roles, 5 handovers
- Data scattered
- Spend, contracts and market data sit in separate systems
- Master data
- Which suppliers belong to the same group is not visible
Example figures from one sprint. Your numbers come out of the interviews.
Process baseline
Effort, roles, degree of automation
For the shortlisted processes we capture what they cost today: frequency, hours, people involved, handovers. That is the numerical basis every use case is calculated against.
Score and cut
Six questions every process has to pass. What fails, fails visibly.
From around 40 processes to 12, criterion by criterion
- Hard P&L effectA bookable euro beats time saved
- Size of the effectAround 1 m€ or a strategic reason
- EvidenceYour own data beats an estimate
- FeasibilityData and systems have to exist
- ScalabilityAcross regions and business units
- New for youWhat you already do does not count
Six criteria
Transparent instead of opinion
Every process is checked on P&L hardness, effect size, evidence, feasibility, scalability and novelty. The result sits on the process, not in a backup chart.
Shortlist, top 12 processes by score
- Category and spend analysisProcurement, external purchase price5.0
- Cash flow forecastTreasury, working capital5.0
- Churn and retentionKey accounts, revenue retained5.0
- Selection and negotiationProcurement, price and payment terms4.9
- Pricing and quotingKey accounts, realised price4.9
- FX exposureTreasury, financial result4.7
Process shortlist
The twelve that are worth it
What remains are the processes with hard leverage, evidence and scale. Use cases are built only for those. That saves the workshop discussion about candidates that would not carry anyway.
Use cases in euros
Three to four concrete use cases per process, each with problem, solution, effect and estimated annual value.
Use case 1.01.01, procurement
HardCost
- Problem
- Indirect spend is spread across categories, suppliers and regions. Pulled together by hand, bundling opportunities stay invisible.
- Solution
- The AI merges spend and contract data and gives buyers a prioritised list of where bundling or renegotiating pays off.
- Effect
- Lower purchase price, bookable in the P&L
3 m€per year, estimated
Cost reduction across the entire indirect spend
Use case studio
Problem, solution, effect, amount
Every use case sits in the same grid and separates hard cost effect, revenue effect and freed capacity. How the amount was derived is laid open and marked as an estimate, so finance can follow the maths.
Top 10 of 36 use cases by estimated annual value
- Bundling and renegotiation analysisProcurement, cost3 m€
- Supplier search, wider bidding fieldProcurement, cost3 m€
- Autonomous negotiation for standard demandProcurement, cost1.5 m€
- Deadline and renewal radarLegal, cost900 k€
- Group-wide churn early warningKey accounts, revenue900 k€
- AI cash flow forecastTreasury, interest750 k€
Ranked by value
The ten with the biggest effect
Out of all use cases come the ten with the highest estimated annual value. That is the basis for the prioritisation workshop where you decide which five get built first.
Make vs. partner
For every top use case a recommendation on how it gets into the company. And why.
Make vs. partner overview, top 10
Make, build it yourself
Bundling analysis in procurementGreenfield on your data, the spend taxonomy is your differentiation
Cash flow forecastModel on SAP sources, no new system
Whitespace for cross- and upsellCompany structures and your own sales data, no vendor knows both
Partner, integrate
Deadline and renewal radarMature CLM market, buy the extraction and connect the escalation
Supplier searchLicense the market data feed, build the ranking yourself
ESG audit evidenceVendors with GRI and CSRD logic already exist
Scaling the pilot applies where something already runs and only needs to grow: churn early warning and autonomous negotiation.
Make vs. partner overview
Build where you differ. Buy where the market is mature.
Make when data and logic are your differentiation. Partner when mature vendors exist and integration is faster than development. Bridgemaker earns nothing from any vendor, so the recommendation stays neutral.
Profile 1.04.01, autonomous negotiation
Scale the pilot
The negotiation bot is productive for long-tail purchases. The work is extending it to standard demand, benchmark prices and writing back into the ordering system.
- Data basisOrder history, vendor master, benchmark pricesReady
- System integrationOrdering system and approval workflowMedium
- RiskCategory fit and approval thresholds, not the technologyLow
- 90-day roadmapCategory rules, benchmark feed, pilot in 2 categories, rollout4 milestones
Build-ready profile
Data, integration, roadmap
Every top use case gets a profile: the solution in plain words, the data needed, how it connects to existing systems, how the value was derived and a 90-day roadmap. Your team or a partner can start from it straight away.
Its own field
Physical AI: when AI reaches into plant and warehouse.
Sensors, cameras, robots and autonomous vehicles. This is where the use cases sit that appear on no office list and usually carry the hardest leverage, because they move downtime, scrap, throughput and safety directly. We treat physical AI as its own search field, with the same six criteria and the same euro logic.
Three layers, three answers, example autonomous plant inspection
- SenseInspection robot or drone, thermography, acousticsPartner
- UnderstandAnomaly detection on your plants and your fault historyMake
- ActWork order to maintenance, adjust the schedule, humans approveMake
Make vs. partner per layer
Buy the hardware, keep the intelligence
Sensors and robotics almost always come from partners, because the market is mature and hardware ages fast. The models on your data and the intervention in your processes belong to you, because that is where the advantage builds.
Typical physical AI use cases, industry and logistics
- Autonomous plant inspectionA robot walks the rounds, AI spots leaks and corrosionDowntime
- Vision quality control in the lineCameras check every part, the model learns from your fault imagesScrap
- Autonomous intralogisticsDriverless vehicles, steered by your order mixThroughput
- Predictive maintenanceSensor data predicts failures, the system plans the interventionStandstill
Physical AI use cases
Four patterns that fit almost every plant
Inspection, quality control, intralogistics and maintenance. What they are worth to you depends on your assets, downtime cost and volumes, so we calculate them on your baseline during the sprint.
Use case map
We draw your use case map once, free of charge.
You name two to five search fields, we deliver a first map with the AI use cases that pay off and, for each one, the call: make, partner or scale the pilot.
Name your search fields. We come back within two working days, the map follows within five.
Rather talk first? We look at your processes together and tell you where the leverage sits.
15 minutes, with a partner.
How we work
We deliver a basis for deciding, not a zoo of use cases.
Bridgemaker runs the sprint, facilitates kickoff and prioritisation and stands behind the numbers. Tautiom is the AI engine we use to map processes, score them and price them in euros. The recommendation stays neutral because we hold no stake in any vendor.
Euros instead of buzzwords
Every use case has an estimated annual value with its derivation laid open and separates cost, revenue and capacity. Finance can follow the maths.
Neutral on make vs. partner
We recommend building only where your data and logic make the difference. Where the market is mature, we say so.
Ready to continue
Profiles with data basis, integration and a 90-day roadmap. Your team or a partner can start the day after the workshop.
Our approach
How it gets into your company.
Three steps, each with a clear result. Before them sits a free use case map on your search fields.
014 weeks
Use case sprint
From the search fields to three to five pitched use cases with annual value and a route to implementation.
- Kickoff: search fields, goals, guardrails
- Process breakdown and baseline, longlist of around 40 processes
- Scoring against six criteria, use case studio, top 10 by value
- Prioritisation workshop and pitch with the make vs. partner call
023 weeks
Deep dive workshops
The chosen use cases become ready for a decision.
- Business case per use case, validated with finance
- Technical feasibility and data readiness with IT
- Stakeholder alignment, ownership and implementation roadmap
The result: a go or no-go per use case, with owner and roadmap.
03after that
Implement: make or partner
The route is set, now it gets built.
- Make: your team builds, we guide or build alongside
- Partner: we help with selection, integration and pilot
- Scale the pilot: rollout plan across regions and units
Your time
Around five hours in the sprint and six in the deep dives. We plan the interviews with process owners together with you.
Your data
EU hosting, NDA before we start, model inventory for your IT. We work with interviews and exports, we need no access to production systems.
Your entry point
A free use case map on two to five search fields. We name the terms afterwards.
References
In use with companies that want AI where the P&L feels it.
Industrial gases, intralogistics, insurance and consumer goods. At an intralogistics group we derived use cases along the entire value chain, at an industrial gases group five search fields turned into 36 scored use cases and a top 10 for the prioritisation workshop.
“Best of AI 2025”
Capital magazine (01/25) for the Tautiom AI® application by Bridgemaker.
Talk to someone who has been through it.
We connect you with an existing client. 30 minutes, without Bridgemaker in the room.
FAQ
What you probably still want to know.
What is in the free use case map?
You name two to five search fields and your industry. We run Tautiom on them and deliver a first map within five working days: the typical processes per search field, the use cases with the biggest leverage and, for each one, a first call of make, partner or scale the pilot. Without your data the figures are industry estimates, in the sprint they become your numbers.
How neutral is the make vs. partner recommendation?
Bridgemaker holds no stake in any software vendor and takes no referral commission. We recommend building when your data and process logic make the difference, and a partner when the market is mature and integration is faster than development. Both come with reasoning in the profile. Whether you then build with us is your decision.
How reliable are the euro figures?
Every figure is marked as an estimate and separates cost effect, revenue effect and freed capacity. The derivation is open: baseline from frequency, effort and hourly rate, leverage from benchmarks and your numbers. In the deep dive workshops finance validates the figures before a use case goes into the budget.
How is this different from our internal use case list?
Three things. First the process breakdown: we start from the work, not the technology, and so find the leverage that sits across departments. Second the six criteria, which let every candidate pass or fail visibly. Third the euro value and the make vs. partner call per use case. Your list is good input, we check it too.
Do you cover robotics and sensors in the plant?
Yes, as its own search field. Inspection, quality control, intralogistics and maintenance run through the same process breakdown, the same six criteria and the same euro logic as office use cases. The difference is the recommendation: hardware and sensors almost always come from partners, models and intervention logic stay with you. Vendor scouting and integration planning are part of the profile.
Where does our data go and how safe is it?
Tautiom runs in the EU. Before we start we sign an NDA, share an inventory of the AI models and providers in use with your IT and agree retention and deletion periods. For the sprint we work with interviews, process documents and exports. We need no access to production systems.
What does it cost?
The use case map costs nothing. Everything after that depends on scope: use case sprint, deep dive workshops, implementation support. We name the terms after the map, together with a recommendation on which entry point makes sense for your company.
Let's talk.
Fifteen minutes are often enough to find the biggest leverage. Tell us what it's about.