70%
Of UK manufacturers are investing in digital tools, yet only 1 in 10 factories is fully digital. Investment is concentrated on machines and the shop floor, not the back office.
Source
Make UK, Making it Smarter, August 2025. [1]
Manufacturing
AI agents built for manufacturing operations.
Manufacturing is a precision environment where every record has to be defensible. To MHRA inspectors. To AS9100 audits. To a buyer reading the certificate of conformance line by line. We design, build, and run AI agents that take on the document load behind your operation, so your people can get back to the work that needs them.
Where The Time Goes
Most UK manufacturers are running on partial digitisation.
You have an ERP. You have a quality system. You have an MES on the floor. And you still have a team of people moving information between them. Re-keying purchase orders. Building manufacturing record books by hand. Drafting non-conformance reports. Chasing supplier confirmations. The shop floor has been digitised. The back office, mostly, hasn't.
Single digits
Generative AI adoption in supply chain and manufacturing, against a backdrop of 79% of companies globally already using gen AI in at least one business function.
Source
McKinsey & Company, State of AI 2025, April 2026. [2]
31%
Share of UK workers' time spent on non-core admin. The highest figure across six European markets surveyed, and the gap that agents close.
Source
Ricoh Europe, European workplace research, April 2026. [3]
The Gap
Digital investment is going into the obvious places. The administrative load has been left to absorb the cost.
The documentation, the supplier admin, the order processing, and the audit prep. That's where a workhorse agent earns its place.
Where Agents Earn Their Place
Four areas where an AI workhorse moves the line.
Below are some examples of workflow areas we can build agents for. The exact steps and outputs are designed around your manufacturing process during a Discovery session.
Purchase order and invoice processing
This could look like an agent that takes a supplier invoice through to a matched, posted, ready-to-pay record in your ERP.
- Invoices read from PDFs, scans, EDI feeds and portal exports
- Line items, prices, tax and delivery references extracted
- A three-way match run against the open PO and goods-received note
- Clean invoices posted straight to Sage 200, Epicor, Infor SyteLine or SAP Business One
- Exceptions routed to AP with the discrepancy already explained
The Output
A matched, coded, posted invoice in your ERP, or a routed exception with the mismatch identified and the supporting evidence attached.
Sales order intake
We might build this as an agent that ingests an incoming customer order, however unstructured, and produces a clean sales order in your ERP.
- Orders read from PDFs, emailed spreadsheets, OEM portal exports and customer-specific formats
- Line items, quantities, part numbers and delivery terms extracted
- Customer SKU codes translated to your internal codes against the customer item master
- Non-standard specifications flagged
- The commercial admin team reviews the order rather than typing it
The Output
A sales order ready for review in your ERP, with item codes mapped, non-standard specifications flagged, and the source document indexed against the order.
Quality records and conformance packs
An agent at this stage could compile the documentation pack that ships with a finished batch or work order.
- Aerospace MRBs, pharma batch records, food HACCP records, automotive PPAP packs
- Inspection data, traceability, calibration records and customer specification references gathered from your quality system and ERP
- Standard sections populated, completeness cross-checked against the customer or regulator requirement
- Missing or out-of-tolerance entries flagged for the quality team
- Human authorisation stays where it has to
The Output
A compiled documentation pack with completeness checked, deviations flagged, and the quality sign-off step queued for the named approver.
Supplier onboarding and queries
Or an agent that takes a new supplier through onboarding and handles the day-to-day queries that come after.
- Data gathering, financial checks, and insurance and compliance documents run and validated
- Missing items flagged, quality approvals tracked
- The supplier record created in your ERP once approvals are in
- Routine queries handled once live: delivery status, PO amendments, document requests, payment chases
- Anything outside scope escalated to procurement with the full context
The Output
An onboarded supplier in your ERP with the documentation pack indexed, and a live response handler for the routine queries that would otherwise sit in your procurement inbox.
Design, Build, Run
Three phases. One system in production.
Most providers stop at the build. We design, build, and operate the agent for as long as it's in production.
Phase I
Design
A 30-minute Discovery session, then a scoped specification.
We map the process with you and tell you honestly whether an agent is a good fit. If it is, we write the specification. If it isn't, we say so.
The Terms
Free 30 minutes.
Phase II
Build
Custom development by senior engineers.
The agent is built around your process, your ERP, your quality system, and your standards. Prompt engineering, output formatting, and evaluation are all built and tested before go-live.
The Terms
Fixed scope.
Phase III
Run
Ongoing management for the life of the agent.
We monitor performance, retrain the model as your process evolves, and maintain output quality. Most AI fails when tested seriously. We handle that testing so you don't have to.
The Terms
Live operation.
Skin In The Game
You only pay when the agent delivers.
Every agent we build starts with a refundable commitment up front. It goes towards the work, and it comes back to you if we don't deliver to the specification we agreed. Once the agent is live, you're billed per output produced.
Failed outputs aren't billed. You don't pay for the model running. You don't pay for seats. You don't pay for infrastructure. The commercial structure is set up so we wear the build risk and the run risk. That's the point.
Designed For Inspection
Built to live in a governance-led supply chain.
Manufacturing covers wider regulatory ground than most sectors we work in. A pharma CMO answers to the MHRA. An aerospace Tier 2 supplier answers to AS9100 audits and ultimately to the CAA. A food manufacturer answers to the FSA and to the BRCGS auditor turning up next week.
We design every agent to fit the documentation regime your sector lives in. GMP and ALCOA+ data integrity in pharma. CAP3064 expectations in aerospace. HACCP and CCP monitoring records in food. HSE, ICO, and BSI requirements, from ISO 9001 to IATF 16949, across the rest. Records are attributable, timestamped, version-controlled, and reviewable. Human authorisation stays human where it has to.
We don't claim adherence to every named standard. We design agents to be ready for them. The Synextra infrastructure underneath has been running governance-led workloads on Azure for many years, with ISO 27001 certification, ICO registration, and UK GDPR compliance at the platform layer. Sector-specific evidence requirements get built into each agent during scoping.
- MHRA
- CAA
- FSA
- HSE
- ICO
- BSI
Common Questions
Questions we hear from firms scoping agents in manufacturing.
The questions below are most likely to come up when we scope agents with mid-tier manufacturers, specialist subcontractors, and family-owned operations.
Will it work with our ERP? We're on Sage 200, Epicor, Infor, or SAP Business One.
Yes. We connect to your ERP via the supported APIs or, where APIs are limited, through middleware or RPA hooks against your existing screens. You don't need to migrate ERP to deploy an agent. Most of the work happens around your ERP rather than inside it. During a Discovery session we map the integration approach against your specific stack.
Our data is fragmented across ERP, MES, PLM, and quality systems. Can you still build something useful?
This is the most common starting point and it isn't a blocker. Agents are built around scoped processes, not whole-data-platform projects. A purchase order matching agent doesn't need a unified data platform. It needs reliable access to the PO and GRN data wherever those live. During a Discovery session we identify what the agent actually needs to read and write, and we work with what's there.
Will AI-assisted quality records pass an ISO 9001, AS9100, or GMP audit?
This question comes up in almost every manufacturing scoping conversation and it has a clear answer. The standards require that records are controlled, accurate, attributable, and timestamped, and that human authorisation sits where the standard requires it. None of those requirements rule out AI-assisted record drafting. They do rule out AI making the final authorisation. We design every agent so the audit trail captures what the agent generated, what data it used, when, and who reviewed and approved the final record. Sector-specific evidence requirements get built into the agent during scoping: ALCOA+ in pharma, deterministic evidence in aerospace.
We don't have an internal IT team to manage AI. Is that a problem?
That's the reason the service exists. We design the agent, we build it, and we run it. Monitoring, retraining, performance evaluation, and output quality are all on us. Senior engineers, not juniors learning on your project. Your team gets the output. Synextra has been running managed Azure workloads for governance-led businesses for many years and that infrastructure underpins every agent.
We tried AI before and the output wasn't reliable enough to use.
Most AI in the market fails a serious scrutiny test. The reason is almost always thin engineering on prompts, evaluation criteria, and output formatting, combined with no one running the model after handover. In a document-heavy manufacturing context, small changes in prompt wording can shift output accuracy by a percentage point or two, which at batch volume is the difference between useful and unusable. Getting that right before go-live, and keeping it right afterwards, is the job we do.
What does it cost and how long does it take to get an agent live?
You pay a refundable commitment per agent up front, then per output once the agent is live. Failed outputs aren't billed. We don't quote build durations without scoping, but a typical agent moves from Discovery to live in weeks rather than months, depending on the process complexity and the state of the source data. Full pricing detail is on the pricing page.
Start Here
Tell us where the paperwork is slowing you down.
Thirty minutes, no obligation. We'll tell you honestly whether an agent is a good fit for the process you have in mind. If it isn't, we'll say so.
30 minutes. No obligation. No sales pitch.
Sources
Stats cited on this page.
- Make UK, *Making it Smarter: Global lessons for accelerating automation and digital adoption in UK manufacturing*, August 2025.
- McKinsey & Company, gen AI adoption in supply chain and manufacturing, set against the State of AI 2025 finding that 79% of companies globally use gen AI in at least one function, April 2026.
- Ricoh Europe, *European workplace research on time spent on non-core administrative tasks*, survey of 6,000 office workers across six European markets, April 2026.