All your company’s AI, managed from one place.
Every use case, its models and tools, what it costs and what it delivers—in plain sight. The evidence you need to decide where to invest, what to scale and what to stop. With the blynt Framework, we turn those decisions into action: organizing your processes, implementing improvements alongside your team and measuring their impact, case by case.
Every use case, its cost and its results in plain sight. With the blynt Framework, we turn those decisions into action, case by case.
Method to decide. Team to build. Platform to measure.
What has improved? From AI adoption to Enterprise AI Capability
A company buys AI licenses for all its employees. Six months later, leadership asks: “What has improved?”
Nobody can answer.
With blynt, the company starts with one well-measured use case. Six months later, the same question.
And this time, there is an answer.
We do not sell today’s tool. We build the capability to adopt tomorrow’s.
Models and tools will continue to change every quarter. What endures is a common foundation and five pillars on which every use case builds.
AI Engineering
Integrate AI into real work, connecting processes, information, systems and human review.
Models & Tools
Select technology, evaluate its performance and ensure it remains fit for purpose.
Governance & Security
Define authorized data, permissions, accountability, controls and traceability.
People & Skills
Develop roles, practical skills, champions and adoption.
Measurement & Improvement
Measure quality, time, costs and outcomes to decide what to continue, improve or stop.
Enterprise Context Layer
The common foundation: your organization’s operational memory, bringing together processes, data, rules, documents, roles and decisions.
Models change. This foundation and these pillars do not.
Read the framework: the six-step cycle, the blynt Score and blynt Maturity. Explore the framework →
AI adoption is widespread. The foundations to sustain it are not.
Surveys published in 2026 point to the same gaps: scale, return, cost and dependence.
scale agentic AI in key functions, although 59% already use it.
are rethinking their approach because of token costs; 82% are concerned about them.
Self-reported responses from different surveys and populations; they are not comparable with each other. EY: US executives. ServiceNow: a vendor survey. These surveys do not demonstrate the effectiveness of blynt’s work.
+40% of agentic AI projects will be canceled before 2028, according to a Gartner projection. Gartner · press release, June 2025. A forecast, not a fact.
Acquiring a tool is straightforward. Building a capability around it takes a method.
Four stages, applied in focused cycles
Each cycle works on a real use case and ends with a decision.
Assess
Understand the process and the organization’s current capabilities.
Design
Define the improvement and the criteria for success.
Enable
Implement the solution and prepare the team to use it.
Evolve
Review operations and refine the solution based on evidence.
A first project in 90 days
- Month 1Initial measurement and design: one team, one process and agreed success criteria.
- Month 2Testing and delivery: a focused solution, applied training and a comparison of results.
- Month 3Adoption and review: results are recorded and the organization decides whether to expand, adjust or stop.
What we need from you: a process owner, a technical counterpart and access to the information for the case.
How we will know it works: with a success criterion you sign before we start.
Indicative timeline: not a commitment to go into production in 90 days.
We keep measured, projected and signed figures apart
- Projection. What could happen if the volume and usage assumptions hold.
- Operational result. What the recorded volume, quality and times show.
- Released capacity. Time freed for other work, with an explicit valuation.
- Financial savings. An amount backed by sources and a statement signed by you.
Released time is not a saving until it is evidenced.
We start with a pilot on one process
In about 90 days you know what AI delivers in that process and what to do next.
How the value pilot works
- We choose the case. A process that matters, an owner who can make decisions and agreed success criteria.
- We measure the starting point. Time, quality and cost of the current process, recorded in the platform.
- We improve it with AI. We test models and tools on your case and compare results with the blynt Score.
- We validate with your team. People review and approve; we measure before and after.
- You decide with data. Scale, adjust or stop, with a PDF report ready for leadership.
Included
- Our team alongside you at every step
- The blynt platform during the pilot
- PDF report for leadership
Duration and scope are indicative and agreed at the start for each case.
The blynt platform
- Use-case journey. Guides each case from definition and initial measurement through analysis, improvement, validation and impact.
- Score and Maturity. Score assesses the performance of each test; Maturity tracks capabilities by team and pillar, with a maturity path for each team.
- Atlas. A map of the organization: contexts, owners and people, in one place.
- Results for leadership. Results summarized in a PDF ready for leadership.
- Enterprise view. Every AI use case in one place: models and tools, costs, results and approvals.
- People decide. The client approves the starting point, the decisions and the operating months.
Other services, once the pilot works
Now available: Enterprise Context, the organization’s shared operational memory. Coming soon: blynt Runner.
The platform records tests, decisions and results. It does not autonomously run or monitor the client’s agent.
We work better with some companies than with others
A good fit if
- You already use AI in a process or plan to.
- Someone owns the process and can make decisions about it.
- Someone on your team can spend a few hours measuring how the work is done today.
Not a fit if
- You only want a slide deck or a trends report.
- Nobody on your side can validate the results.
- You want us to run your systems for you.
Within the EU AI Act, with people in charge
Minimal or limited risk
We work on use cases with minimal or limited risk under the EU Artificial Intelligence Act (AI Act). We do not take on prohibited practices and, if a use case could be high-risk, we tell you before we start.
Your data does not train public models
We set up and review your AI tools so that company and personal data are not used to train public models.
People decide
Your team reviews and approves the results before they are used. We agree with you how each use case is supervised and we review results to catch errors and bias.
What people ask us before they start
What does blynt labs do?
We help you decide with data which AI use cases to invest in, what to scale and what to stop. We start with a pilot on a real process, measure it with your team and record the results in the blynt platform.
How long does a pilot take?
About 90 days. The timeline is indicative, not a commitment to go into production: it depends on scope, permissions, data and your team's availability.
What do you need from us?
Three things: someone who knows the process and can make decisions about it, someone from IT who can give us access, and real examples of the work (documents, data or cases) to measure the before and after.
Who approves the results?
You do. Your team approves the starting point, the decisions and the operating months. You sign the success criterion before we start.
Does the platform run our AI agent?
No. It records tests, decisions and results. It does not run or autonomously monitor the client's agent.
What if AI does not improve the process?
You will see it in the data. At the end of the pilot you decide whether to scale, adjust or stop, with a PDF report for leadership.
See a complete use case in 30 minutes
We walk you through it start to finish, with sample data. Bring a process you have in mind and we will tell you whether it is a good first case.
- We reply within 1 business day with a few possible times.
- On the call we walk through a complete use case and look at your process.
- If we go ahead, we send you the scope and the success criterion in writing.