Soroco vs KYP.ai: Work Graph and Agentic Process Intelligence Compared

Soroco Scout is a process intelligence platform that builds a work graph, a map of how teams experience digital work, from interactions observed on user machines. KYP.ai is an agentic process intelligence platform that captures user activity across desktops and virtual machines, correlates it across users and applications to reconstruct end-to-end process flow, attaches a financial value to every inefficiency it finds, and generates production-ready agent code.  

Both Soroco and KYP.ai read task interactions at the workstation where system event logs cannot reach, which puts them in the same broad category of activity-centric process intelligence solutions. They diverge on three things that decide most evaluations: which machines the agent runs on, how licensing shapes how much of the workforce you can afford to observe, and what the platform hands you at the end.  

Soroco Scout fits teams that need to understand work friction and simulate workflow changes. KYP.ai fits organizations that need a continuously updated, ROI-ranked automation pipeline across a large distributed workforce, including virtualized desktop estates. 

Key takeaways

• Both Soroco and KYP.ai observe digitalized work at the workstation-level, so the usual process mining objection about event logs missing manual work does not separate them. 

• The UK government’s G-Cloud 14 service listing for Soroco Scout states that Scout “only operates on Windows desktop machine.” KYP.ai runs across Windows, macOS, Citrix and VDI environments. 

• Published G-Cloud pricing for Scout is £800 per user per year on one listing and £1,700 per license on a reseller listing. Per-seat pricing turns population coverage into a budget decision. 

• KYP.ai runs at less than 2% CPU and has been deployed across more than 10,000 concurrent workstations, with statistically relevant insights inside three weeks and measurable returns inside 90 days. 

• KYP.ai produces something Scout does not: an ROI-ranked automation pipeline and production-ready agent code that runs on whatever automation platform you already use. 

How this comparison was made

What was evaluated: Soroco Scout and the KYP.ai process intelligence platform, on six criteria weighted for enterprise buyers running distributed knowledge work. Capture architecture and estate coverage (25%), population coverage and continuity (20%), output artifacts (20%), deployment model and time to insight (15%), privacy architecture (10%), commercial transparency (10%). 

Evidence base: vendor documentation from both companies, UK G-Cloud 14 public procurement listings for Scout, Gartner Peer Insights market listings, independent buyer guides, and KYP.ai deployment data drawn from live enterprise implementations. 

Last verified: September 2026. 

What Soroco Scout does

Soroco is an enterprise work intelligence company. Its Scout platform installs an agent on user machines, observes interactions such as clicks and keystrokes, and assembles what the company calls a work graph, described on its own site as “a map of how teams experience digital work” derived from team machine interactions. 

The work graph is the product’s organizing idea. Instead of reporting on one person’s task sequence, Scout aims to show where friction sits inside a team’s digital work, which applications a process passes through, where handoffs stall, and which steps vary between people doing nominally the same job. Soroco states that its dataset covers 300 trillion interactions a year and that it works with more than 200 customers. 

The 2026 positioning has moved toward AI agents. Soroco describes Scout as a platform that observes humans and agents operating together and then simulates the consequences of a workflow change, and it argues that agents built from documentation “inherit what is written, not what actually happens.” The company claims 30% to 40% reductions in process effort and two to four weeks to a full operational picture. 

Privacy is handled through consent and anonymization. Soroco states that Scout collects only opted-in data, does not single out individuals, and uses anonymized user IDs. 

Two operational details are worth knowing before an evaluation, both of them documented in public procurement records. The UK Government G-Cloud 14 listing for Scout states the platform “only operates on Windows desktop machine,” and it sets out an onboarding process in which the supplier guides the customer through firewall requirements, information security review and desktop installation, with onsite support available at extra cost. An independent buyer guide reaches a similar conclusion, noting that Scout’s “integration depth appears more service-led than self-serve” and that commercial transparency is low because pricing and packaging are not publicly clear. 

What KYP.ai does 

KYP.ai is an agentic process intelligence platform. It captures user activity across desktops and virtual machines at population scale, correlates that activity across users and applications to reconstruct how a process actually moves through the organization, quantifies the financial cost of each inefficiency it finds, and generates production-ready agent code that runs on whatever automation platform the customer already operates. 

The platform rests on three pillars. The 360 Enterprise View captures and correlates process, people and technology data across every desktop, application and system in real time. The Business Transformation Engine turns that raw activity into a quantified opportunity list, so an automation candidate arrives with a business case attached instead of a hunch. The Agentic AI Enabler supplies the business context and the executable code that AI agents need to act, and it exposes process intelligence through the Model Context Protocol so agents can query it directly at runtime. 

The distinction the Business Transformation Engine is built around is the difference between what could be automated and what should be. Most discovery tools produce the first list. The second one requires attaching a dollar value and a volume to every candidate, which is what turns a discovery exercise into a funded program. 

On deployment: setup takes minutes, the platform is live in days, statistically relevant insights arrive within three weeks, and measurable returns land inside 90 days. The agent runs at less than 2% CPU and has been proven across more than 10,000 concurrent workstations, on Windows, macOS, Citrix and VDI. 

On privacy: KYP.ai is privacy-by-design. Sensitive data is anonymized at source, on the workstation, before it leaves the device, and granular configuration lets an organization define exactly what is and is not captured. No sensitive information is processed or transferred externally. The platform holds GDPR, SOC2 Type II and ISO27001 certification. 

In short: KYP.ai is process mining plus task mining in one platform for full work visibility, and the process intelligence layer for agentic AI readiness. 

Where the two platforms actually differ

Roughly 70% of knowledge work never touches a system event log. That is why both platforms exist, and it is why neither one is a substitute for traditional process mining. The differences that decide between them sit elsewhere. 

Assess the scale and scope of your process intelligence need

This is the least discussed criterion in process intelligence evaluations and the one most likely to end an evaluation early. The organizations that most need work observation run large distributed operations in business process outsourcing, global business services, shared service centers and banking back offices. Those environments are rarely uniform Windows fleets. They run Citrix and VDI for security and cost reasons, they carry macOS populations across engineering and design functions, and they mix corporate and client-supplied images across delivery centers. 

If the capture agent covers part of that estate, the visibility covers part of the process. A claims workflow that touches a Citrix-hosted application and a locally installed spreadsheet appears as two disconnected fragments, and the handoff between them, which is usually where the cost sits, stays invisible. The published G-Cloud service definition for Scout is explicit that it operates on Windows desktop machines, and it repeats the point twice under service constraints. KYP.ai captures across Windows, macOS, Citrix and VDI, which is why it can hold a single view of a process that crosses those boundaries. 

Anyone evaluating either platform should ask for a written statement of supported environments against their own estate inventory. It is a five-minute question with a large consequence. 

How to evaluate licensing cost and total cost of ownership

Soroco does not publish pricing on its website. Two public UK procurement listings do: £800 per user per year on the direct G-Cloud 14 listing for Scout, and £1,700 per license on a reseller listing from Agile Business Process UK Limited. Note: these prices reflect 2024 UK public sector framework terms, and an enterprise price book may read differently. 

Per-seat licensing means the cost of observing the organization scales linearly with how much of the organization you observe, which pushes buyers toward a defined population, typically one department, one delivery center or one process family. That is a rational commercial response, and it is why task mining engagements so often begin scoped even when the platform is capable of more. 

The scoping has an analytical cost. A bounded population produces a bounded view, and conclusions about the wider organization then rest on extrapolation from that sample. Extrapolation works when the observed group is representative. It breaks when it is not, and in multi-geography operations it usually is not, because the same nominal process runs differently in Manila, Kraków and Bogotá for reasons that have nothing to do with the people involved. 
 
KYP.ai offers a free 7-day trial and total engagement costs depend on the scope and scale of the enterprise need. You can assess indicative cost implications through KYP.ai’s ROI calculator.  SPS deployed KYP.ai across 8,500 employees in 20 countries and identified 874 hours per month of recoverable effort in customer experience, 599 in finance, 496 in HR and 543 in supply chain management, alongside a 25% improvement in productive capacity. Those figures are not projections from a sampled group. They are counts drawn from the whole observed population, which is why the finance function was willing to underwrite the business case built on them. For an accurate estimate, contact KYP.ai directly. 

How to choose between Soroco and KYP.ai 

Both Soroco Scout and KYP.ai observe digital interactions on the workstation level. The evaluation usually turns on what they hand back in actionable insights. 

Scout’s output is the work graph and, in the 2026 product, simulation of what a workflow change would do. That is a strong artifact for a business operations team trying to understand its own work and test a redesign before committing to it. 

KYP.ai’s output is a costed process improvement pipeline and executable code. Every inefficiency it surfaces carries a dollar value and a volume, which is what a CFO needs to fund the work and what an automation center of excellence needs to sequence it. The platform then generates production-ready agent code with the business context attached, and that code is platform agnostic by design: deployable on UiPath, SAP Joule, n8n, Camunda, Power Automate, WatsonX, BluePrism, ServiceNow, CrewAI or Anthropic, with no lock-in to KYP.ai’s own runtime. 

The key question is whether you are looking for work productivity diagnosis and a funded plan for improvement. Whether that gap matters depends entirely on which problem you have. If your organization already knows what it wants to change and needs to understand the work well enough to design the change, the diagnosis is the deliverable. If your automation pipeline has been a wish list for two years because nobody can rank it by value, the costed pipeline is the deliverable. 

When Soroco Scout is the better choice

Scout is the stronger fit when the objective is understanding team-level work friction in depth, particularly in a Windows-standard environment where estate coverage is not a constraint. It suits organizations that want to simulate the effect of a workflow change before implementing it, and that have the internal appetite for a supplier-guided onboarding process with allocated business subject matter experts. 

According to customer reviews on Gartner Peer Insights and G2 it may also suit buyers who want a partner-led engagement over a platform they operate themselves. The service-led delivery model that a buyer guide flags as a transparency issue is, for some organizations, exactly the model they want. 

When KYP.ai is the better choice

KYP.ai is the stronger fit for organizations above roughly 1,000 knowledge-work employees running distributed operations across mixed desktop environments, where the requirement is continuous visibility across a moving operation. It suits teams that need every opportunity to arrive with a business case attached, and that are trying to move AI agents out of pilot by giving them real operational context in place of documentation. 

It fits organizations with an automation program, a center of excellence or a continuous improvement practice already running. KYP.ai can accelerate an existing process transformation program, or act as a catalyst to create one. 

Key limitations of KYP.ai

Any platform worth evaluating has a shape, and the shape rules some buyers out. Three things to know before shortlisting KYP.ai. 

1. KYP.ai does not read event logs.

It captures how work actually gets done at the desktop, including the emails, spreadsheets, decisions and manual steps between transactions that event logs never record. If the requirement is transaction analysis inside an ERP, a system-native process mining platform covers that directly and KYP.ai does not replace it. The trade is deliberate. Event logs are a proxy for how work happens and desktop observation is the record of it, and which one you need depends on where your cost sits. 

2. KYP.ai is not a process modeling or BPMN authoring environment.

Organizations that need a governed system of record for how processes are defined should look at a modeling suite. KYP.ai reports what happens, not what was supposed to happen. 

3. KYP.ai requires an agent on employee machines, and a conversation with employees about it.

Capture runs through a lightweight agent at less than 2% CPU across Windows, macOS, Citrix and VDI. Sensitive data is anonymized at source, on the workstation, before it ever leaves the device. No sensitive information is processed or transferred externally, granular configuration defines exactly what is and is not captured, and the platform holds GDPR, SOC2 Type II and ISO27001. None of that removes the need to consult works councils in several European jurisdictions and to tell employees plainly what the platform does with their data. Deployments that skip that step meet resistance the architecture cannot solve. 

A pilot checklist for either platform

Before signing anything, get written answers to these: 

1. Which operating systems and virtualization environments does the capture agent support, tested against your own estate inventory? 

2. What is the measured CPU and memory footprint on a standard corporate image, and has it been validated at your intended concurrency? 

3. How many users does the pricing model make it realistic to observe, and what does the analysis look like at that population, as against the ideal one? 

4. What exactly is anonymized, at what point in the pipeline, and can the customer configure it per data type? 

5. What does the platform produce that a business case can be built on, and can you see a redacted example from a comparable customer? 

6. How long from contract to statistically relevant insight, and what does the vendor commit to in writing? 

7. What professional services are mandatory as opposed to optional, and what do they cost across a three-year term? 

Bottom line on our Soroco vs. KYP.ai comparison

Soroco Scout and KYP.ai answer the same underlying complaint, that the most expensive part of enterprise work is invisible to the systems meant to report on it. They answer it differently. 

Three points to carry into an evaluation. Estate coverage is a feasibility question, not a feature question, and it should be settled first. Licensing shape determines how much of your organization you can afford to observe, which determines whether your conclusions rest on counting or on extrapolation. And the output artifact, a work graph or a costed pipeline with executable code, decides whether the project ends with a better understanding or with a funded program. 

Most environments are live within days. Book a demo to see what full work visibility looks like across your own estate, virtual desktops included. 

Frequently asked questions