ReshapeX: The knowledge grounding layer for industrial AI [Skip to main content](#main-content)[Skip to navigation](#navigation)[Skip to footer](#footer) ![](/_next/image?url=%2Fimages%2Fhomepage%2Fhero-machined-parts-flatlay.jpg&w=3840&q=75&dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) AI agents for industrial sales & support # Sell more.Answer faster.Add capacity,not headcount. Virtual inside sales, apps engineering & support for OEMs, distributors & manufacturers. Book a demoContact us ![](/_next/image?url=%2Fimages%2Flibrary%2Fparts-distribution-warehouse.jpg&w=3840&q=75&dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) Two ways teams put agents to work ## Cut the busywork. Capture the revenue. Labor savings ### Add capacity, not headcount. Virtual inside sales, applications engineering, and customer support handle the repetitive part-number lookups, cross-references, stock checks, and quotes — so your team spends its hours on the accounts and problems that need a person. * Inside sales * Applications engineering * Customer support Revenue generation ### Turn inbound into quotes, faster. Put the agent on your website and in your inbox. It answers buyers the moment they ask — cross-references, approved substitutes, stock, pricing — grounded in your catalog, and hands your team a ready-to-price opportunity instead of a lead gone cold overnight. * On your website * In your inbox * Grounded in your catalog From the field ## The proof is alreadyin production. [![Novanta / ATI Industrial Automation robotic tool-changer](/_next/image?url=%2Fimages%2Fcase-studies%2Fati%2Fhome-featured-banner.webp&w=3840&q=75&dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) ![Novanta](/images/logos/customers/novanta-1.svg?dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) Case study · Novanta ### How Novanta gave every customertheir own application engineer. Read the case study→ ](/en/case-studies/item-expert-agent) 400+ Sessions, 100% accurate 24/7 Always on, in production 7 Languages from launch 8M+ Valid configurations NOVT Novanta · NASDAQ WHAT GOES WRONG ## Hallucinations aren't a bug in the model. They're how LLMs work. Hallucinations aren't a bug in the model.They're how LLMs work. Drive configurations, fieldbus compatibility, firmware revisions, approved substitutes: your team lives in the exceptions. A model trained to sound fluent will miss the edge first. Our agents answer from your catalog and your equipment docs, and they cite the source, never the open internet. [Read why hallucinations aren't a bug to patch →](/insights/hallucinations-are-not-a-bug) The model that sends your customer the wrong motor protection relay sounds exactly like the model that sends them the right one. WITHOUT THE LAYER ## General AI vs. ReshapeX A confident wrong answer costs more than no answer. Generic AIReshapeX If 3RV2031-4BA10 is unavailable, what is the approved substitute that preserves Class 10, A-release 14…20 A, N-release 260 A, and screw terminals? ### Generic AI 3RV2031-4BA15 is a direct drop-in replacement: identical ratings, same approvals, no changes needed. ⚠ Hallucinated: a plausible MLFB with the wrong release range, stated with full confidence and no citation. * Guesses on industrial product specifics (drives, fieldbus modules). * Hallucinates part numbers, and your customers notice. * Requires manual verification of every claim. * Your application engineer reverts to spreadsheets. * Rolls back by attrition as users lose trust. ### ReshapeX Recommended substitute MLFB: 3RV2032-4BA10. Preserves Class 10, A-release 14…20 A, N-release 260 A, and screw terminals; UL/CSA approvals unchanged. 3RV2 cross-referenceUL/CSA approval matrix ✓ Grounded: verified against your catalog before it reaches a customer. * Grounded in your real catalog and pricing rules. * Quotes with verified line-card accuracy in seconds. * Every answer cites the exact SKU, page, and rule. * Confidence thresholds route edge cases to human experts. * 99.9% measured accuracy on your actual data. The 99.9 proof Accuracy on your own catalog 99.9% Not a benchmark. Evals from your real inbound and RFPs; answers that fail never reach a customer. $2M+Year-1 opportunity\* < 12 wkEngagement to production 3–5×More leads * Knowledge base· * Tool harness· * Evals· * Continuous sync Standard AI ceilings ~80%. Grounded layer + harness + evals = the other 19.9%. \*Conservative US-only model anchored on a major industrial OEM's service revenue base; global ceiling scales to $4M+ per deployment. ![](/_next/image?url=%2Fimages%2Flibrary%2Fparts-workshop-floor.jpg&w=3840&q=75&dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) WHAT SITS UNDER YOUR AGENTS ## One verified layer underneath every agent. Built at ingest, not at query time, reviewed by your experts, reached through a purpose-built tool harness. From raw inputs through structure and human review to a published grounding layer and ongoing sync, then the agents we build, you build, or you already run, all on one foundation. 01 Bring it in ERP, PIM, PDFs, the web, and the people who hold tribal knowledge: everything that should inform an answer. → 02 Shape the graph Compatibility, substitutes, drive configurations, firmware lines: the messy catalog story becomes structured truth before a customer asks. → 03 Review with experts When sources disagree, your team decides what wins: no silent rewrites, no mystery updates. → 04 Publish the layer The picture of your line card agents actually query: stable, sourced, ready for the tool harness on every turn. → 05 Keep it current Taxonomy, pricing, and stock refresh on the cadence your business needs, so yesterday's truth does not become tomorrow's mistake. DOWNSTREAM * Agents we build Support, quoting, apps engineering, ops: same grounded foundation, tuned to how you work. * Agents you build You steer prompts and workflows; the knowledge grounding layer stays the single source of truth. * Agents you already run Beneath the copilots you already use, so reps get catalog-backed answers instead of confident guesses. ## USE CASES IN PRODUCTION USE CASES IN PRODUCTION Real questions. Grounded answers. Sourced. From RFP to Validated BOMQuotes with Pricing & ComplianceTechnical Answers, VerifiedLeads Straight into CRMApproved SubstitutesOne Part Number from SpecsDatasheet in One Click From RFP to Validated BOM demo loading ![](/_next/image?url=%2Fimages%2Fhomepage%2Ftwo-paths-technicians-collaborating.jpg&w=3840&q=75&dpl=dpl_HvgJBdVtjznds4dDP8tgd1EkuWM3) Path A · MCP ## Bring your own agents. You already use Copilot, Claude, ChatGPT Enterprise, or your own AI team's agents. We expose ReshapeX as an MCP server. Your agents call it. Accuracy jumps from a generic-AI ceiling to **99.9% on your catalog.** * CPMicrosoft Copilot * CLClaude * GPTChatGPT Enterprise * +Your custom agents * Your team owns the agent layer * ReshapeX exposed as a typed MCP server * Knowledge layer maintained by us, continuously * Live in weeks · no migration Path B · FDE ## We build the agents. You don't have an AI team, or you want the full solution. Our forward-deployed engineers embed with your senior team and ship production agents: RFP→BOM, Quote, Support, Substitute, running on the same grounded knowledge layer. * RFP → BOM Agent * Quote Agent * Support Agent * Substitute Agent * Forward-deployed engineer on site * Production agents in your stack, your domains * Built once, owned by you * Same 99.9% measured accuracy SAME FOUNDATION, EITHER WAY ### The ReshapeX product knowledge layer Your catalog · compatibility rules · approved substitutes · datasheets · proposal archive · pricing tiers 99.9% Measured accuracy TRUST & GOVERNANCE ## Built for regulated workflows and skeptical operators. Your data stays yours. Every answer is sourced. Every high-stakes call routes to a human. * ### Data permissions Role-based access. VPC deployment available. No training on your catalog. No cross-customer data. * ### Logging & auditability Every query, source, and output logged. Exportable to your SIEM. * ### Human approvals Confidence thresholds you set. Below threshold, the answer routes to your expert, not guessed. * ### System integration Read-access, minimum-privilege connectors. Never elevates beyond what you grant. [Read the trust answers →](/en/faq#faq-cluster-trust-accuracy) > “Most AI on a website waits for you to ask and forgets you the moment you leave. The item agent is part of item's journey, not a box bolted onto it. It recognizes the customer, it carries the conversation forward, and it can reach out with the right thing at the right time. An answer is the start of a relationship, not the end of a transaction.” IN THEIR WORDS ## Real work, real results.Real work,real results. Most industrial AI projects plateau around 80% accuracy — close enough to demo, not close enough to trust. The engineers and operators in these stories chose a different path: knowledge grounding built at build time, not query time. Their agents don't hedge. They cite firmware revisions, fieldbus compatibility charts, and approved substitutes. That's not a lucky run. That's what happens when the graph is right. [Read all case studies →](/en/case-studies) From the Field ## What practitioners say “ > The fact that my customers go to the agent and find this info is gonna save me a lot of time. I spend 10–15 minutes on that every time, and now it takes me less than 1 minute. Account Manager · Large distributor · 25 yrs in industry “ > I find it very interesting that you come from the automation industry — the learning curve is much shorter, which hasn't been the case with consultants who take a while to understand our business. CEO · CNC distributor · LatAm “ > Wow, with this tool I can probably do 20× more custom quotes per week. Inside Sales · Value-added distributor “ > I was texting my boss saying this is exactly what I've been asking for! Technical Support Specialist · Mid-size distributor · 20 yrs in industry “ > I can immediately see how this can be useful. Product Manager · Large distributor · 30 yrs in industry “ > Trying to temper my enthusiasm here, but your AI is wildly encouraging. It opens a lot of doors and possibility — there are so many ways that we, and our distributors, could and should be using this. VP · Large OEM “ > Whoa...I can finally retire! Inside Sales Specialist · Large distributor · 40 yrs in industry TALK TO US ## Give us your twenty hardest questions. We'll demo on your SKUs, run your evals, and show citations for every answer. * Real Examples * Working Demo * Your Data Be the team that defends every answer and ships AI in months, not years. Schedule a meeting Talk to the agent first