Search helps you find information. AI can understand your business, work with your data, and execute real business processes.
Prakreon builds AI systems for real business work.
We start with one process that takes up your team's time, measure it, and only then talk about building anything. Sometimes the honest answer is that AI is the wrong tool.
30 minutes on one process.
Free
A written report, measured from your records.
Free for our first clients
A working system inside the tools you already use.
Fixed quoted price
Monitoring, fixes and accuracy checks.
Annual
You have information. The work has not started.
The work is done. People make the decisions that need judgement.
Not a platform you migrate onto. Systems that fit the processes, data and tools you already have.
Turn unstructured documents into structured, usable business information.
Invoices, specifications, certificates, reports, scanned paperwork. The information exists, but the only way to use it is for a person to read it and type it out again. We build systems that read documents the way a person does and return structured data a process can consume.
Connect information, decisions and actions across business processes.
Work that follows rules, runs often and consumes a real share of somebody’s week. We put intelligence at the specific step where reading, interpreting or drafting is currently manual, and leave the judgement where it belongs.
Systems that collect, validate, analyse and report business information.
Where an organisation has to demonstrate something — to a standard, a regulator or a customer — the difficulty is rarely the reporting. It is that the underlying data is scattered and hard to substantiate. We build systems where evidence stays attached to the figures derived from it.
AI solutions for specialised business requirements.
Most real problems do not arrive pre-labelled. Where a requirement does not fit an existing product or pattern, we design and build for it directly — including concluding that AI is not the right answer.
Systems we have built and continue to develop. Both came from problems that turned up in real work, not from a technology looking for a market.
Connects the weighing balance to the BIS hallmarking portal.
At an Assaying and Hallmarking Centre, every article in a consignment has to be weighed, tagged and photographed, and each value typed into the BIS HUID portal by hand. BISBridge connects the balance directly to the portal, so the weight goes from the instrument into the right field without anyone reading a display and retyping it.
An ESG operating system built around evidence.
ESG reporting is a data problem before it is a writing problem. The information sits across utility bills, invoices, certificates and site records, and the figure that reaches the report is usually separated from whatever proves it. The ESG keeps them attached — from the source document through to the disclosure.
Each of these replaced work that was being done by hand. No client is named — most of this sits inside processes our clients would rather not discuss publicly — but the mechanism is described in full.
Turning scattered product, pricing and specification information into a consistent quotation, without retyping it every time.
Read how it was builtContinuous monitoring of tender sources, so relevant opportunities surface instead of being discovered too late.
Read how it was builtSeparating the few tenders worth reading in full from the many that are not.
Read how it was builtTurning documents into business data — not just readable text, but structured information a process can use.
Read how it was builtRecognise your own process in one of these? Describe it and we'll tell you what we think — including if AI is the wrong tool for it.
Book a 30-minute callAn implementation sequence. The deliverable is a working system inside the business, not a recommendation.
The process, the data and the outcome.
What the work actually involves today, what information it depends on, where that information lives, and what a better result would look like. We start from the business process, not from the model.
Turn documents and knowledge into structured intelligence.
Most business information is unstructured — documents, spreadsheets, email, things people know. Before AI can work with it reliably, it has to become structured, typed and traceable. This step is usually where the real work is.
Design and implement the system.
The workflows, models, interfaces and checks that do the work. Built to the shape of the process rather than the other way round, and no more complex than the problem requires.
Connect it to the tools already in use.
A system that lives beside the business gets ignored. We put it inside the tools your team already works in, so the improved way of working is also the path of least resistance.
Measure accuracy, reliability and business impact.
Whether the output is correct, whether it holds up on real data, and whether the process is actually better. If a step is not carrying its weight, it changes or it goes.
A system that is confidently wrong is worse than one that does nothing, because the error propagates quietly. These are the properties we build for.
Outputs are derived from your data and documents, not from what a model recalls about the world.
Every extracted value keeps a reference to where it came from, so any figure can be checked against its source.
Results are checked against the rules, requirements or constraints they are supposed to satisfy.
Typed fields rather than free text, so downstream systems can consume them and errors surface as errors.
Messy, inconsistent and incomplete inputs are the normal case. Systems are built expecting that, not assuming clean data.
Anything ambiguous is flagged for a person rather than guessed at. Judgement and approval stay with your team.
We start with the business problem, not the AI model. If AI is the wrong tool for it, that is a legitimate answer and we will say so.
Business information is messy, fragmented and largely unstructured. Our systems are designed around that reality rather than around a clean demo dataset.
The objective is a working system that fits into the business and survives contact with it — not a pilot that impresses and then gets quietly abandoned.
BISBridge and The ESG exist because the underlying problems came up in real work, repeatedly. They are not technology demonstrations looking for a market.
The common thread is business information: a lot of it, often in documents, and currently handled by people because until recently nothing else could.
Start with one process that takes up your team’s time. A free 30-minute call is enough to tell whether it is worth measuring.