AI Agents for Manufacturing
FISTA Solutions builds manufacturing AI agents that live outside the control path: drafting and updating work instructions, supporting defect classification, summarizing planning scenarios, extracting supplier documents, and answering maintenance history questions — with engineering and quality approval on anything that reaches the line.
- 150+
- projects delivered
- 50+
- companies served
- 99.9%
- verified uptime
- 47%
- efficiency gains
- 12+
- countries reached
What we build
What can AI agents do in manufacturing?
Manufacturing agents draft work instructions from engineering changes and floor feedback, classify defects with similar historical cases retrieved, summarize scheduling trade-offs, extract supplier certificates and test reports, and answer technician questions from work order history with citations.
- 01
Work instruction agent
Drafts and updates instructions from engineering changes and floor feedback, with engineering approval before release.
Documentation - 02
Defect triage support agent
Classifies defects from images and notes, retrieves similar cases, and proposes containment for quality review.
Quality - 03
Planning scenario agent
Summarizes scheduling trade-offs against demand, capacity, and materials for a planner to decide.
Planning - 04
Supplier document agent
Extracts certificates, test reports, and packing documents into structured records tied to lots and orders.
Supply - 05
Maintenance history agent
Answers technician questions from work order history and manuals with citations, cutting diagnosis time.
Maintenance
Requirements
What guardrails do manufacturing agents need?
Manufacturing agents sit near safety-critical processes and quality systems, so guardrails are strict: no control-path access, approval before anything reaches the line, traceability into quality records, and evidence retained to the standard your quality system expects.
| Guardrail | Why it matters here | How FISTA implements it |
|---|---|---|
| No control access | Agents must never influence machine behavior. | Read-only acquisition through historians or OPC UA gateways, with no write path from any AI component to control systems. |
| Approval before the line | Wrong instructions cause scrap and injury risk. | Engineering and quality approval gates before any instruction or containment action is released to operators. |
| Quality record integrity | Outputs may become part of a quality record. | Traceable outputs with source citation, versioning, and reason-for-change captured where records are amended. |
| Domain grounding | Generic answers are worse than none on a shop floor. | Retrieval restricted to your approved documents, drawings, and history, with abstention when coverage is missing. |
| Shift usability | Operators cannot fight an interface during production. | Short, scannable outputs designed for shop-floor screens, tested on the hardware in use. |
Where AI fits
Which manufacturing workflow should you automate first?
Start with the maintenance history agent or supplier document extraction. Neither touches the line, both save measurable time immediately, and they establish the retrieval quality that instruction drafting will later depend on.
- 01
1. Answer maintenance questions
Technicians lose hours to history hunting; retrieval with citations returns that time without touching production.
- 02
2. Extract supplier documents
Certificates and test reports are structured, repetitive, and entirely back-office.
- 03
3. Support defect triage
Classification and similar-case retrieval speed quality review while quality staff keep disposition authority.
- 04
4. Draft work instructions
Only after retrieval quality is proven, and always behind engineering approval before release.
- 05
5. Add planning support
Scenario summarization helps planners once the underlying data has demonstrated it is trustworthy.
Cost and timeline
How much does an AI agent for manufacturing cost, and how long does it take?
Cost is driven by document and history digitization, integration depth, and approval workflow; timeline by quality review and plant access. FISTA does not quote blind: the scoping call returns an agent design, a grounding plan, and a phased estimate.
Content readiness governs value. Agents retrieving from scanned binders and inconsistent naming perform poorly, so digitization and metadata work is often the first real task. FISTA assesses your document estate and prices that preparation honestly rather than hiding it.
Approval workflow determines adoption. Instruction drafting only helps if engineering review is fast, so the review interface is designed with the agent, with change highlighting and one-click approval.
Send the scope you have, even if it is a paragraph. You get a written brief, an architecture sketch, and a phased estimate before any commitment.
Get a scoped quoteDelivery
How does FISTA deliver an AI agent into production?
FISTA delivers agents in four gated phases: a discovery sprint that picks the workflow and writes the agent specification, a design that names tools, permissions, and approval points, a build with an evaluation harness and shadow runs on real work, and a production release with traces, dashboards, and rollback.
- 1
Select and specify
Choose the workflow with a measurable outcome, map its systems and edge cases, and write the agent spec with success metrics.
OutputAgent specification, golden test set
- 2
Design the guardrails
Tool inventory with least-privilege scopes, approval gates, escalation paths, data handling, and the evaluation plan.
OutputTool and permission matrix
- 3
Build and shadow-run
Implement tools as MCP servers or connectors, iterate against the evaluation harness, and run in shadow mode on live inputs.
OutputShadow-mode results, eval scores
- 4
Release and observe
Graduated rollout, full traces, cost and quality dashboards, on-call runbook, and a change process that re-runs the evals.
OutputProduction agent with SLOs
Why FISTA
Why choose FISTA Solutions to build your manufacturing agents?
FISTA builds plant-adjacent agents with a hard control boundary, retrieval restricted to your approved content, and approval gates before anything reaches an operator. Work is contracted through a US entity with full IP assignment.
Manufacturing specifics
- No AI component has a write path to control systems; acquisition is read-only through historians or gateways.
- Retrieval is restricted to your approved drawings, instructions, and history, with abstention when coverage is missing.
- Engineering and quality approve before any output reaches an operator, and the approval is recorded.
- Outputs are short and scannable, tested on the shop-floor hardware your shifts actually use.
How FISTA engineers
- Spec-Driven Development: every deliverable starts as a written specification with acceptance criteria, so scope is testable before it is built.
- AI-native delivery: engineers direct coding agents under review gates and evaluation harnesses, compressing build time without loosening verification.
- Official Anthropic partner, with production experience across Claude, OpenAI, Google, and open-weight models, chosen per workload rather than by default.
- One accountable delivery lead, weekly demos on your environment, and code in your repositories from week one.
What you get as a client
- 150+ projects delivered for 50+ companies across 12+ countries since 2017, with 99.9% verified uptime on systems we operate.
- A US entity (FISTA Solutions Inc., Wilmington, Delaware) for contracting, invoicing, and IP assignment, with an engineering center in Faisalabad, Pakistan for cost-efficient senior capacity.
- US business-hours overlap for standups and reviews; written decision logs so nothing depends on a meeting you missed.
- Flexible engagement: fixed-scope build, embedded forward deployed engineers, or a dedicated team that you can scale month to month.
Clear answers
What teams ask before deploying agents.
Straightforward guidance for evaluating scope, fit, and the next step.
01Will an agent ever control equipment?
No. FISTA architects manufacturing agents with read-only data acquisition and no write path to control systems, and documents the boundary so your OT and safety teams can verify it rather than take it on trust.
02Can AI generate work instructions?
It can draft and update them from engineering changes, existing instructions, and floor feedback, with engineering approving before release. The agent reduces authoring time; accountability for what reaches the line stays with engineering.
03Can agents help with quality disposition?
They can classify defects, retrieve similar historical cases, and propose containment, which speeds review. Disposition remains with quality staff, and the record shows the human decision and its basis.
04Our documents are scanned binders. Does this still work?
Not well, until they are digitized and indexed. FISTA assesses the document estate in discovery and prices the preparation work, because retrieval quality is what determines whether the agent is useful on the floor.
05How do you avoid generic, unhelpful answers?
Retrieval is restricted to your approved content, answers cite the source document and revision, and the agent abstains when coverage is missing rather than producing plausible-sounding generic guidance.
06How long until it is useful?
A maintenance or supplier document agent is typically useful within weeks where content is already digital; instruction drafting follows once retrieval quality is proven. Discovery sizes the digitization work first.
Continue exploring
Related capabilities
Scoped in writing before you commit
Give the floor answers without giving up control.
Bring the maintenance questions, the supplier paperwork, or the instruction backlog. The scoping call returns an agent design and a phased estimate.