# AI Consulting Engagement Models and Pricing: A 2026 Buyer's Guide > Source: https://netray.co/resources/ai-consulting-engagement-models-pricing > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Knowledge Base ## Short answer AI consulting engagement models compared: pilots, retainers, fixed-fee builds, and outcome pricing, with 2026 rate benchmarks for manufacturing AI projects. ## Category erp-general ## Content **Intro:** AI consulting engagements in 2026 follow four pricing models: scoped pilots ($25,000-$150,000), fixed-fee production builds ($100,000-$750,000), monthly retainers ($10,000-$60,000), and outcome-based pricing tied to measured savings. Hourly rates for AI consultants run $150-$400, with ML engineers at $175-$275 and AI architects at $250-$400. For manufacturers, the highest-ROI engagements target ERP-adjacent problems - quote automation, planning optimization, document processing - where data already lives in SyteLine or LN. This guide explains each model, when it fits, and the pricing benchmarks that keep proposals honest. **Sections:** #### The Four Engagement Models and When Each Fits **Body:** Scoped pilots prove one use case on your data in 6-12 weeks for $25,000-$150,000; they fit first AI initiatives where feasibility is genuinely uncertain, and a good pilot contract defines the production-readiness criteria up front so success has a next step. Fixed-fee builds deliver a production system - an AI quoting agent, a document-extraction pipeline, an on-prem LLM deployment - for $100,000-$750,000 with milestone acceptance; they fit well-defined problems with stable requirements. Retainers at $10,000-$60,000 monthly fund a continuous AI team across a roadmap of use cases and fit companies past their first win. Outcome-based deals price against measured results, such as a percentage of documented labor savings, and fit mature buyers with instrumented baselines. **Bullets:** - Pilot: $25K-$150K, 6-12 weeks, contract must define production criteria - Fixed-fee build: $100K-$750K with milestone acceptance payments - Retainer: $10K-$60K/month for a continuous roadmap-driven team - Outcome-based: fees tied to measured savings, requires baseline data #### 2026 Rate Benchmarks by Role and Firm Type **Body:** Individual rates vary by role: data engineers bill $150-$225 per hour, ML engineers $175-$275, LLM application developers $175-$300, and AI solution architects $250-$400. Firm type moves those numbers substantially. Big Four and global SI AI practices quote blended rates of $300-$450 and rarely engage below $500,000. Specialist AI boutiques blend at $200-$300. AI-native firms that use their own agents in delivery blend at $140-$225 with materially faster timelines. Offshore AI development at $50-$100 per hour exists but struggles with the domain context manufacturing problems demand - and is disqualified outright where training data includes ITAR technical data or CUI, which covers most defense-manufacturing use cases. #### What Manufacturing AI Projects Actually Cost End to End **Body:** Realistic all-in figures for common manufacturer use cases: an AI document-processing pipeline for supplier certs, POs, and material test reports integrated to your ERP runs $75,000-$200,000 to production. An AI quoting assistant that reads RFQ packages and drafts estimates from SyteLine cost history runs $100,000-$250,000. An on-premises LLM deployment - open-weight models such as Llama or Mistral variants on your own GPUs for CUI-safe usage - runs $150,000-$400,000 including hardware sizing (typically 2-8 GPUs, $60,000-$250,000 capex), model deployment, retrieval infrastructure, and security hardening aligned to NIST SP 800-171. Ongoing model operations and evaluation typically cost 15-25% of build cost annually. Treat any proposal without an operations line as incomplete. **Bullets:** - Document AI pipeline with ERP integration: $75K-$200K to production - AI quoting assistant on ERP cost history: $100K-$250K - On-prem LLM deployment for CUI-safe AI: $150K-$400K plus GPU capex - Annual AI operations and evaluation: 15-25% of original build cost #### Contract Terms That Separate Good AI Deals from Bad Ones **Body:** AI contracts need clauses traditional IT agreements lack. Define acceptance quantitatively: extraction accuracy thresholds (for example, 95% field-level accuracy on a held-out document set), latency targets, and evaluation datasets agreed before build starts - "working demo" is not acceptance. Secure IP ownership of fine-tuned model weights, prompts, and pipelines; some firms retain model IP and rent it back. Prohibit training on your data for other clients' benefit, in writing. For defense manufacturers, require data-residency terms keeping all training and inference inside your boundary or a FedRAMP-authorized environment, with US-persons-only access where ITAR applies. Finally, demand a documented handover package - evaluation harness, retraining runbook, monitoring dashboards - so you are not permanently dependent on the builder. #### How Netray Prices AI Consulting for Manufacturers **Body:** Netray specializes in exactly this intersection: AI systems built on ERP data for regulated manufacturers. Our engagements start with a fixed-fee AI Readiness Assessment ($15,000-$30,000, 3-4 weeks) that inventories your SyteLine or LN data, ranks use cases by ROI, and produces a costed roadmap. Production builds are fixed-fee with quantitative acceptance criteria, and because our delivery teams use Netray's own agent platform, build timelines run 30-40% shorter than conventional AI consultancies at blended effective rates of $140-$200. For defense clients, we deliver fully on-premises stacks - open-weight models, private retrieval, NIST SP 800-171-aligned hardening - with US-persons-only teams, keeping CUI and ITAR data inside your boundary. Clients own all weights, prompts, and code outright. **Cta:** Get a costed AI roadmap for your manufacturing operation - Netray's fixed-fee AI Readiness Assessment ranks your use cases by ROI in under a month. **Faq:** #### How much does AI consulting cost in 2026? **Answer:** AI consulting rates in 2026 run $150-$400 per hour depending on role and firm type: ML engineers bill $175-$275, AI architects $250-$400, and Big Four practices blend at $300-$450. Scoped pilots cost $25,000-$150,000, production builds $100,000-$750,000, and monthly retainers $10,000-$60,000. AI-native firms that automate their own delivery blend at $140-$225 with faster timelines than traditional consultancies. #### Should I start with an AI pilot or go straight to production? **Answer:** Start with a pilot only when feasibility is genuinely uncertain - novel data, unproven accuracy requirements, or untested integration paths. For well-established patterns like document extraction, RFQ processing, or ERP data chatbots, feasibility is settled and a pilot mostly adds cost and delay; a fixed-fee production build with quantitative acceptance criteria is more efficient. If you do pilot, contract the production-readiness criteria and follow-on pricing up front so success has a defined next step. #### Can AI consulting be done on ITAR or CUI data? **Answer:** Yes, but the architecture and staffing must change. Commercial cloud AI APIs are generally off-limits for ITAR technical data; instead, deploy open-weight models on-premises or in GovCloud-class environments, with encryption, access controls, and audit logging aligned to NIST SP 800-171 and your CMMC 2.0 Level 2 posture. Consulting teams must be US persons with documented CUI-handling procedures. Expect on-prem AI programs to cost $150,000-$400,000 plus GPU hardware, versus cloud-based equivalents. ## Related Slugs - erp-managed-services-pricing-guide - erp-staff-augmentation-vs-consulting - infor-partner-selection-guide ## Search terms AI consulting pricing, AI consulting engagement models, AI consultant hourly rates 2026, on-prem AI deployment cost, manufacturing AI project cost --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json