How Rémis Works

A structured diagnostic that scores your company across five readiness dimensions — data infrastructure, team capability, process maturity, budget alignment, and strategic clarity. You answer 13 questions, and the platform computes a composite score, positions you against a modeled industry distribution (an illustrative estimate, not a live peer database), and generates a personalized action plan with specific quick wins you can execute this week at zero cost. You receive a scored assessment with dimension breakdown and action plan.

Your answers are scored client-side using weighted dimension formulas before anything leaves your browser. Once you request the analysis, your profile is enriched with a server-computed percentile against a modeled reference distribution (an illustrative estimate, not a live database of real assessments). The AI narrative layer receives your raw scores, specific answers, industry-specific benchmarks with citations, and (for higher-readiness companies) a filtered tool catalog with real pricing — all injected as grounding context so recommendations are data-backed, not generic.

Industry-level AI adoption analysis that shows where your sector stands on AI readiness — adoption rates, typical ROI ranges, top use cases, and a modeled peer distribution. Complete a self-assessment to see where you land against a modeled distribution for your industry — an illustrative estimate, not a measured ranking of real peers.

Benchmark data is drawn from a curated industry dataset built from named research reports and surveys. When you complete the self-assessment, a server-side engine places your score against a modeled reference distribution for your industry — an illustrative estimate, not a live cohort of real assessments. The AI analysis layer receives your score, the modeled percentile, and industry statistics with source citations to produce a contextualized positioning report.

The flagship tool. A full consulting-grade AI implementation plan covering tool recommendations with curated catalog pricing, financial projections across three scenarios, a change management plan with industry-specific objection handling, and a week-by-week 90-day implementation roadmap. This is the document you hand to your CFO or business partner. You receive a 10-section implementation plan, exportable as PDF.

This is a multi-stage pipeline, not a single AI prompt. Stage one selects and prices specific tools for your company's stack, constraints, and geography. Then a deterministic financial engine computes TCO, ROI scenarios (downside/base/upside with quarterly ramp), sensitivity analysis, and breakeven projections — these numbers are computed server-side with real math, not generated by AI. Stage two produces the full narrative report using the locked financial facts, a standardized evaluation framework, industry-specific change management data, and live web research for current market pricing. The financial projections are computed server-side. This is a key trust differentiator: the AI narrates the numbers, but it cannot change them.

Monte Carlo-style ROI modeling that runs entirely in your browser. Define the processes you want to automate with real hours, costs, and automation rates, and the simulation engine produces P10/P50/P90 scenarios over 18 months with sensitivity analysis showing which assumptions matter most. You receive scenario-based projections with sensitivity analysis and optional AI narrative.

A client-side simulation engine runs 500 iterations with randomized variance based on your confidence level (conservative 30%, moderate 20%, aggressive 10%). Results are sorted into probability percentiles and charted with confidence bands. Sensitivity analysis tests each variable independently at ±20% to identify the biggest swing factors. An optional AI narrative layer explains the results in plain English, identifies the highest-impact process, and contextualizes your projections against industry benchmarks — but the numbers themselves never touch a server.

Priced tool recommendations calculated at your actual volume — not the marketing page price. For each use case you define, the platform researches candidates, computes monthly costs with full math (base + per-seat + usage + add-ons), checks compliance certifications, maps integration compatibility with your stack, and produces a structured comparison brief with negotiation guidance. You receive a formatted comparison brief with real pricing for each recommended tool.

A two-stage pipeline: first, your raw form input is normalized into a structured specification with validated use cases, volumes, and budget constraints. Then a research stage performs live web searches to find current pricing, verify compliance certifications, and evaluate integration compatibility — every recommendation must include real pricing with source URLs, and the output is validated against a strict schema before delivery. If validation fails, the system retries automatically. Every price includes the calculation math so you can verify it yourself.

A plain-English regulatory brief for the specific AI tools you plan to use, in your specific state and industry. Each tool gets a compliance card with certification status, identified gaps, required contracts (BAA, DPA), data residency information, and the exact question to ask the vendor before signing. You receive per-tool compliance cards with gap analysis and vendor questions.

Tools are matched against an internal compliance catalog with known certifications and common compliance claims. Applicable regulations are identified by your geography and industry combination — HIPAA, SOC 2, CCPA/CPRA, state-specific AI laws, and more. The analysis layer performs live web research to cross-reference each tool against the vendor's actual trust and security pages, checks certification currency, and produces a per-tool compliance brief with gap analysis and a prioritized action checklist.

Live pilot monitoring that converts your 90-day implementation plan into a tracked project. Set milestones with target weeks, track KPIs with baseline and target values, and get weekly status digests that summarize progress, flag risks, and recommend specific next-week priorities. When a milestone gets blocked or a KPI goes off-track, the recommendation engine provides targeted advice grounded in real tool alternatives. You receive weekly status digests and targeted blocker recommendations.

Milestone and KPI tracking runs client-side in your browser. When you generate a weekly digest, the AI receives your structured project data — milestone statuses, KPI trends, completion rates — and produces a concise status update suitable for email or Slack. A separate recommendation engine handles blocked milestones and off-track KPIs, receiving the specific blocker details along with tool catalog data so it can suggest concrete alternatives with real pricing rather than generic advice.

An AI-powered marketing audit that scores your current marketing across five dimensions, recommends specific AI marketing tools with evaluation matrices, and projects ROI with a break-even analysis. Includes a content strategy showing what AI should handle versus what stays human, and a 60-day implementation plan. You receive a full marketing audit with scored dimensions and a 60-day implementation plan.

Your marketing profile is analyzed alongside a server-side ROI computation engine that estimates labor costs, time savings, and break-even months based on who handles your marketing, your team size, and your budget. The AI analysis layer receives these locked financial projections along with industry marketing benchmarks, a standardized evaluation framework for tool comparison, and live web research to discover industry-specific marketing tools beyond the baseline catalog. The evaluation matrices use consistent weighted criteria across every assessment.