One team from the first question to the running system.
From AI consulting and custom development to implementation and integration, we work with enterprises to turn a business need into a working system. An engagement can draw on our portfolio, our proprietary models, or technology developed around a specific challenge, with inference and GPU infrastructure to support it.
Because we build our own models, we can tell you when an existing one will do and when it will not. Not every engagement needs a new model. Every engagement needs the right one.
Where should we start?
AI strategy that ends in a decision, not a slide deck.
Most organizations have more possible uses for AI than they can pursue. AI strategy consulting with Bynn starts from the work: which decisions are slow, which processes depend on people moving information between systems, and where better evidence would change an outcome.
We help you choose where to begin, define the problem precisely and agree what the system must achieve, including how it will be measured and where people stay in the loop.
01Find the opportunity
Map processes and decisions where AI can make a measurable difference.
02Define the problem
Turn a broad ambition into a specific task with inputs, outputs and limits.
03Set the bar
Agree how success is evaluated before anything is built.
Can you build AI around our data and our problem?
Custom AI, built around the work you do.
Custom AI development at Bynn draws on the same research behind our portfolio: decision models, forensic models, age estimation and autonomy. When an existing model fits, we adapt it. When a problem is new, we develop the model, decision engine or autonomous system it needs.
Your data and your requirements shape the system: what it must recognize, what it must decide, how fast, and how it explains itself.
Models
Specialist models trained or adapted for your inputs, from documents and images to text and sensor data.
Decision engines
Systems that return typed decisions with a confidence, ready for software to act on.
Autonomous systems
Agents and mission executives that coordinate several steps toward a goal.
How do we turn a pilot into something our organization can use?
Bring AI into your existing systems.
A model only creates value when it is connected to the systems where work happens. Our AI implementation and integration services connect AI to your data sources, applications and workflows, so it receives the right information and its output reaches the place it is needed.
Integration includes evaluation: testing the system on your own data, agreeing the thresholds at which it acts alone, and deciding what happens when it is unsure.
In
Your systems
- Data sources and documents
- The applications your teams use
- Events from existing workflows
The system
Model or decision engine
- Tested on your own cases
- Thresholds at which it acts alone
- A defined path when it is unsure
Out
Where the work happens
- A record updated
- A case routed
- A person asked to review
01Connect
Integrate with the systems your teams already use, through APIs and existing workflows.
02Evaluate
Test against your own cases before the system acts on live work.
03Hand over
Agree who operates the system and how it is monitored once it runs.
Can AI do the work across several steps and systems?
Autonomous workflows for complex operations.
An autonomous workflow does more than answer a question. It interprets what arrives, decides what to do, coordinates the next step and acts, across several systems if needed.
In insurance, that means requesting the documents a claim needs in the claimant's language, following up on what is missing, examining the evidence and routing the claim. Workflows run autonomously by default, with optional human review whenever an agent is unsure how to proceed.
Interpret
Read documents, images and messages as they arrive.
Decide
Choose the next step with DecisionNode or a model built for the task.
Act
Send the request, update the record, route the case, or ask a person.
How will it run, and who provides the stack?
Inference and infrastructure, as part of the system.
Every AI system needs somewhere to run. Bynn brings together model serving, inference and GPU resources as part of the stack an engagement needs, alongside the models and workflows themselves.
Deployment environments and operating terms are agreed for each engagement, around your requirements for data location, security and scale.
Model serving
Serve the models and decision engines a system depends on.
Inference
Run inference for workflows and applications, including DecisionNode's inference service.
GPU resources
Provide the compute an engagement needs to train and run its models.
How an engagement works
Every engagement is scoped to the challenge, so the shape varies. These are the stages most of them pass through.
Discover
We learn how the work is done today: the people, systems, documents and decisions involved.
Define
We agree the problem, what the system must achieve, how it will be evaluated and where people review its work.
Build
We adapt existing models or develop new ones, and assemble the decision logic and workflow around them.
Integrate
We connect the system to your data and applications and evaluate it on your own cases before it acts on live work.
Operate
The system runs on agreed infrastructure, with monitoring and the human review points you defined.
Timelines, service levels and commercial terms are agreed for each engagement. We do not publish generic delivery promises.
Built on technology we already run.
An engagement can start from Bynn's portfolio: ZOREAL for identity, trust and document forensics, Agemin for age assurance, Detector24 for media forensics, DecisionNode for decisions and Zora for autonomy research. That means less to build from nothing, and models already at work in our own products.
Digital trustHuman trust for digital interactions: identity verification and document forensics in ZOREAL Verify, verified meetings, sign-in and signing.
Age assuranceAI for age assurance, built on Bynn's facial age-estimation research.
Media forensicsSpecialist models that examine what AI can create and conceal in images, video, audio and text.
Decision intelligenceA decision model and inference service that returns decisions connected systems can act on.
Autonomy / ResearchA mission executive and autonomy engine for autonomous systems, demonstrated in simulation.
Research with its evidence attached.
The models an engagement draws on are measured. Independent results and Bynn's own evaluations are shown separately, each with the conditions that stay attached to it.
Independent evaluation
72.53%
True-positive rate, ages 13-16
#1 for true-positive rate in NIST's Child Online Safety evaluation for ages 13-16.
Bynn's facial age-estimation model, which powers Agemin, achieved a 72.53% true-positive rate: the proportion of people aged 13 to 16 correctly estimated within that age band.
- Measured by NIST in its ongoing evaluation program. NIST evaluation is not certification or endorsement.
- The result measures age estimation within the 13 to 16 band. It does not measure a reduction in online harm.
NIST results table last updated 29 September 2026
NIST FATE Age Estimation & Verification. Submission bynn-000.Bynn preliminary evaluation
81.6%
Mean accuracy, 15 text suites
81.6% mean accuracy across 15 text suites in Bynn's preliminary October 2026 evaluation.
DecisionNode MoE's result in Bynn's preliminary October 2026 evaluation. The suites contain 25,134 items and cover a range of decision tasks. The published comparison includes results where other models lead.
- Bynn's own preliminary evaluation, run on development splits. Not an independent result.
- A mean across suites, not a guarantee of accuracy on any single task.
Preliminary results, October 2026
DecisionNode benchmarks and methodology. Preliminary results, October 2026.
Questions enterprise buyers ask
Do we need to train a new model?
Often not. Many problems can be solved by adapting an existing model or combining our portfolio's models in a workflow. We develop a new model when the problem calls for one.
Can you work with our existing systems?
Yes. AI implementation and integration is part of every engagement: connecting to the data sources, applications and workflows your teams already use.
How do you decide when AI acts on its own?
Together with you, during definition and evaluation. We agree the confidence thresholds at which a system acts alone and the cases that always go to a person.
Do you provide the infrastructure as well?
We can. Model serving, inference and GPU resources can be part of an engagement. Where and how the system runs is agreed around your requirements.
Is this consulting or software?
Both, depending on what the challenge needs. AI strategy consulting is a common starting point, and it leads into development, integration and operation by the same team.
Which industries do you work with?
Our deepest work is in banking and insurance, especially document fraud and claims. Our capabilities also apply to energy and utilities, retail, healthcare, telecommunications, public services, smart cities, public safety and defense.
How do we start?
Book a meeting and bring a challenge. The first conversation is about your work, not our products.
Bring us the challenge.
Tell us about the decision, the process or the problem. We will tell you honestly what it would take to address it with AI.