The Integrated Engineering Advantage: Zero Translation Gaps.

One integrated engineering team spanning eight disciplines. No handoffs between hardware, software, data, and AI specialists.

• Most industrial AI projects fail because requirements get lost between three or four specialist teams.
• RAIISS engineers work across PLC hardware, cloud infrastructure, full-stack software, and AI architecture — in the same heads, on the same deliverables.
• Your domain expertise goes in; working software comes out. Nothing gets lost in translation.

Proof of Concept in 2 weeks. Production deployment in 4-6 weeks. Managed service ongoing. Typical enterprise AI timelines are 12-18 months.

• We skip the multi-year roadmaps, the stakeholder sign-off gauntlets, and the endless architecture review boards.
• Our POC gets your data indexed and queryable within 2 weeks, with a benchmark-based success criterion agreed upfront.
• If the POC fails to meet the benchmark, you apply 100% of the cost toward deployment — or walk away. No sunk costs.

DomainRAG deployment runs $50-75K. Typical enterprise AI engagements for equivalent capability run $500K-$3M.

• Enterprise consultancies staff three-to-fifteen people on an engagement. We deliver the same scope with an AI-accelerated team that stays lean by design, so you pay for outcomes instead of overhead.
• Our POC tier starts at $10K with a money-back-toward-deployment guarantee.
• Our managed service is $25-50 per user per month — priced to scale with your team, not to lock you in.

Prompt-engineering approaches hallucinate on structured data. Our RAG-first architecture retrieves and cites — it never invents.

• Generic LLMs try to stuff your spreadsheet into a context window. By row 500, they forget what the columns mean.
• DomainRAG uses tabular chunking: column headers are preserved in every chunk, so the vector math captures the relationships between data points.
• Every answer cites specific data points — CAS numbers, row references, file sources — so your team can verify the answer against the source data.

The same platform works across food science, specialty chemicals, manufacturing, process industries, and software engineering.

• Our first case study (Flavor Science RAG) indexed 400,000 records across five public databases. Our second (Code RAG) handles 47 file types of source code.
• Same tabular chunking. Same Azure AI Search. Same C# orchestration. Only the domain data changes.
• Whatever your industry, if the value lives in structured data, DomainRAG applies.

Five products on one unified stack: edge connectivity, cloud visibility, HMI/SCADA, predictive AI, and domain-specific knowledge engines.

• FlowBridge brings your field data to the cloud. PlantPulse turns it into MES visibility and OEE dashboards.
• AutoAutomate replaces legacy HMI/SCADA with modern WPF + TwinCAT 3. IntelliInsight layers predictive analytics on top.
• DomainRAG stitches proprietary knowledge into the picture. Start anywhere; scale up as you grow.

RAIISS products run on our managed Azure infrastructure. You pay a subscription; we handle hosting, updates, security, and scaling. Your data is always exportable in standard formats.

• Default model is managed service: we host, we maintain, you use. If you stop paying, access ends — but your data comes with you in standard formats (no data lock-in).
• DomainRAG supports ephemeral indexing inside our managed environment: spin up an index, run your analysis, securely delete when done. Pay only for compute time used.
• Enterprise tier available on request for customers who require customer-hosted deployment and code ownership — priced as a premium, with maintenance responsibility transferring to the customer.

Decades of combined experience across factory-floor automation and enterprise cloud. Our team writes PLC code in the morning and vector search algorithms in the afternoon.

• The AI consulting market is flooded with developers who have never touched a PLC, walked a production floor, or read an OPC UA trace.
• Our engineering DNA is industrial-first. We understand ADS, IEC 61131-3, SCADA, recipe management, SPC, OEE, and CMMS — and we understand how they connect to modern cloud AI.
• That context matters when your AI has to reason about your real operations, not a sanitized tutorial dataset.