Pattern intelligence across all active consulting engagements
Across 6 consulting clients in 5 countries — spanning manufacturing, automotive, industrial machinery, LED distribution, LED manufacturing, and healthtech — one pattern appears with near-perfect consistency: companies have modern ERP or CRM software (SAP, Salesforce, Odoo, Impulsa) but run their actual day-to-day operations on WhatsApp, email, and Excel.
The most acute version: inbound requests (discount approvals, service inquiries, product matching, purchase authorizations) arrive via email or WhatsApp and require a human to manually validate against ERP/catalog data, then respond — every single time. At Grupo Lamosa: 30–40 emails/day from one salesperson. At Aronlight: 200–300 inbound requests/day. At AutoalDia: 10–15 WhatsApp inquiries daily with no CRM for the service team.
The opportunity: an AI middleware layer that sits between the inbound channel (email / WhatsApp) and the ERP/database, applies business rules, and reduces 80% of decisions to a single click. The Lamosa engagement has already designed this architecture — "El Validador Inteligente." The product question is: can it be packaged for 1,000 companies with the same problem?
Market validation: Mercura (YC W25, $2.1M seed) just launched targeting this exact space for inbound RFQ automation. The outbound proposal generation half of the problem — 700 proposals/week at Aronlight — remains wide open. Composite score: 23/25. Confirmed in 4 of 6 clients called.
Confirmed = pain validated in discovery call or proposal. Inferred = from pre-call research only. Confirmed carries 3× weight in scoring.
Frequency score = (confirmed clients × 3) + (inferred clients × 1). Confirmed pains from actual calls or proposals only.
None of the above products intercept an unstructured email approval request, automatically retrieve the relevant ERP/pricing record, and present a pre-validated recommendation inline so the manager can approve in one click from their inbox — no portal login required. Pipefy and Kissflow require requests to enter their system. ApproveThis has no AI reasoning. SAP tools require full SAP adoption. The missing product is an AI layer that works on top of whatever currently exists (email + Excel + ERP) without requiring behavior change. This is especially acute for LATAM and Southern European mid-market companies where ERP adoption is partial and operational communication is entirely email/WhatsApp. The Lamosa "Validador Inteligente" architecture fills this gap exactly.
Workflow automation market: $23.77B in 2025 → $37.45B by 2030 at 9.52% CAGR. [Mordor Intelligence]. No clean TAM exists for "email-native approval triage" specifically — this is a feature gap inside a large market, not a named category yet. SAP Business One alone has ~30,000 mid-market customers globally. Even 0.5% penetration at $800/month = $144M ARR.
All current players treat WhatsApp as a customer-facing support or marketing channel. None provide a two-way operational layer where a sales rep can type "¿qué stock tenemos del SKU 45143?" in WhatsApp and have the system fetch it from SAP in real time. The missing product is an AI agent that speaks ERP fluently and lives inside WhatsApp — not a CRM that syncs messages after the fact, but a live query/action layer that makes the ERP accessible without a login. This gap is most acute in mid-market LATAM companies where WhatsApp is the operating system but SAP/Odoo/Salesforce sit idle. None of the funded players (WATI, Respond.io, Treble.ai) have built this bridge.
Conversational commerce in LATAM: estimated $18.2B in 2025, 35% YoY growth, ~72% flowing through WhatsApp. [AuroraInbox]. Over 40% of Mexican businesses conduct procurement via digital channels, up from 25% in 2021. B2B e-commerce in Brazil grew 26% in 2025. WhatsApp Business economy estimated at $45B globally. [Invent]
Mercura raising $2.1M from YC confirms the space is real and early. But their focus is inbound RFQ automation for manufacturers receiving quote requests. The gap they leave open: the mid-market LATAM/Southern European distributor who needs to proactively generate outbound proposals — where the sales rep pulls pricing from Odoo, applies client-specific margin rules stored in Excel, generates the PDF, and sends it. PandaDoc and Proposify have no ERP integration. DealHub targets SaaS companies. PROS targets large enterprise. No current product solves the outbound proposal flow for Odoo mid-market distributors with 500–50,000 SKUs in LATAM. Aronlight is the exact wedge client to prove this architecture.
CPQ global market: $3.14B in 2025 → $7.55B by 2031 at 15.74% CAGR. Manufacturing leads adoption at ~31% market share. [Mordor Intelligence]. AI CPQ implementations report 75% reduction in quote generation time and 23% increase in close rates. [MobileForce]. Large enterprises hold ~71% of current CPQ market — mid-market remains underserved and is the primary growth vector.
For each client: the Mercura feature that comes closest to their pain, and exactly where the product breaks down. This is the map of where AdapttoAI wins.
Mid-market to enterprise B2B wholesale distributors and manufacturers in DACH (Germany-first). Minimum bar: SAP ERP + hundreds of daily inbound RFQs. An external customer sends a spec document — Mercura reads it and generates the quote back. 100% Europe. Zero LatAm. Zero US (expansion "planned", not live).
Vendavo is the $100K+/year pricing optimization platform for companies like Emerson, Ford, and Volvo. They solve the same margin problem AdapttoAI solves — but for enterprises with SAP, a pricing team, and 12 months to implement. They define the ceiling; we define the entry point.
Vendavo proves the pricing governance problem is a real, funded category — $84-100M ARR selling it to the enterprise. They don't go below $1B revenue. Their implementation takes 6-18 months with an SI partner. Their LatAm presence = one Brazilian petrochemical company.
These are the closest geographic competitors — LatAm-native, WhatsApp-first, and growing. But they solve a different layer: shared inbox + lead funnel, not approval governance. Understanding where they stop is understanding where AdapttoAI starts.
Treble.ai is what WhatsApp marketing automation looks like when you build it right: YC-backed, Tiger Global-funded, Meta official partner, 2,000+ clients in LatAm. They dominate the campaign + lead-qualification layer. The gap: they stop exactly where AdapttoAI starts — approval governance, ERP integration, commercial operations.
The scene, at every client:
A salesperson sends a WhatsApp message or emails an Excel attachment: "Can I give this client 18% on SKU 45143?" The manager opens the file, finds the right tab, eyeballs the margin column, checks the promotional grid in a second spreadsheet, and types back "OK" — or doesn't respond for three hours because they're in a meeting. The salesperson follows up. The client is waiting. This happens 30 to 40 times a day.
Why the ERP doesn't solve it:
Every one of these companies has an ERP. SAP, Salesforce, Odoo, Impulsa. The ERP has the pricing rules, the stock levels, the margin data. But no one opens the ERP to answer a discount email. It would require logging in, navigating to the right module, looking up the SKU, and cross-referencing three screens. By the time a manager does all that, it's faster to just remember the rule from experience. So the ERP becomes a system of record for what happened — not a tool that shapes what's happening. The actual decisions run on institutional memory, Excel tabs, and WhatsApp.
The architecture — already proven with Lamosa:
The manager never opens the ERP. The salesperson gets a faster answer. Every decision is traceable. The tool fits the way people already work — no behavior change required. First results are visible in week 1.
Why Mercura validates this — and where the gap is:
Y Combinator just backed Mercura ($2.1M, W25) to solve a related but different problem. In Mercura's world, an external customer sends a request for quote (RFQ) to the company. The AI reads it and generates the quote document that gets sent back. It's customer-to-company communication, automated.
What we're solving is different. Here, the salesperson already has a customer on the line and needs permission from their own manager before they can close. The request travels internally — from sales rep to commercial manager — and it needs a decision, not a document. Mercura has no answer for this.
What internal approval governance actually means:
Right now, "approval governance" at these companies is: the manager's judgment, stored in their head, delivered by WhatsApp. No rules written down. No audit trail. No way to know whether the same discount request gets a different answer on a Tuesday versus a Friday. Approval governance means turning that into a system: define the rules once (margin floors, stock thresholds, exception SKUs), enforce them automatically, and log every decision with the reason. The manager stops being a bottleneck and becomes a reviewer — only called in when the situation is genuinely ambiguous. That layer, built on top of the ERP data companies already have but never expose, is what no one has productized for the mid-market.
Build for Lamosa, Eurostar, Aronlight as custom engagements. $15–30K per build. Extract the reusable components. Lamosa IS the MVP client — architecture already scoped.
Package as a single platform with one ERP connector built once and reused across all modules. Track A (Commercial): email/WhatsApp intake + rules engine + approval UI. Track B (Ops): procurement intelligence + maintenance tracking + SKU performance. The connector is the moat — once plugged into a client's SAP or Odoo, each new module is a sales conversation, not a new integration. Three tiers, billed annually: Core $18K/yr (1 module, up to 500 req/month) · Growth $42K/yr (multi-module, 2,000 req/month) · Enterprise $78K/yr (multi-subsidiary, ERP write-back, unlimited). A manager spending 3+ hours/day on approvals costs $20–32K/year in labor — Core pays for itself in weeks.
Land in one company on one module, expand across both tracks and all subsidiaries. MAGG is the first client where both tracks apply simultaneously. Lamosa Peru → Argentina → Spain. Franchised rollout through SAP/Odoo/NetSuite implementation partners — they do the connector, we do the modules.
Track A and Track B are not two products. They are two surfaces of one platform, sharing a single ERP connector. The connector is built once per client — every additional module is a sales conversation, not a new integration project. That is the moat.
Quick win on commercial approvals. ERP connector built. Track B (ops intelligence) becomes a natural upsell 3 months later.
Ops pain is the door opener — NetSuite timing creates urgency. ERP connector built. Track A (distributor approvals) is Phase 2 once inside.
No competitor publishes pricing. Estimates below are derived from job postings, ARR/customer count back-calculation, and category benchmarks.
| Player | What they solve | Motion | Est. ACV | Market |
|---|---|---|---|---|
| Mercura | External RFQ automation (customer sends quote request, AI responds) | Sales-led, demo-gated | $25K–60K/yr | DACH, German-speaking |
| Vendavo / Pricefx | Enterprise CPQ and pricing optimization | Enterprise, 6-18 month cycles | $100K–150K/yr | US/EU enterprise |
| WATI / Respond.io | WhatsApp messaging platform (no ERP logic, no approval rules) | Self-serve / PLG | $1.2K–6K/yr | Global SMB |
| Our target position | Internal approval governance — salesperson asks manager, AI pre-filters, manager one-clicks | Consulting-led → SaaS, annual billing | $18K–78K/yr Core $18K · Growth $42K · Enterprise $78K |
LatAm + EMEA mid-market |
The pricing gap is the opportunity. Mercura starts at ~$25K/year and requires a 3-6 month enterprise sales cycle with German-speaking AEs. At $18–78K/year (annual contract, three tiers), we price on ROI — not on what feels safe. A manager spending 3+ hours/day on approvals costs $20–32K/year in labor alone; the Core tier pays back in weeks. The ceiling of our range ($78K) sits just above Mercura's entry point, creating room to grow upmarket without conceding the mid-market. All tiers are billed annually — standard for ERP-integrated SaaS with meaningful onboarding. The first 3 consulting clients fund the build; the fourth client pays for the product.
What to build, for whom, in what order, and how to price it. ✓ = confirmed in call or proposal · ✗ = wants it but blocked from using Mercura · ~ = inferred, not yet confirmed
| Workflow | Lamosa | Aronlight | Eurostar | AutoalDia | MAGG ~ | Mercura | Priority |
|---|---|---|---|---|---|---|---|
| Inbound Request → Quote Aronlight Module 1 — confirmed in proposal |
— | HIGH ✓ | MOD | — | HIGH ~ | Partial* | MVP — Aronlight |
| Spec / Product Matching Aronlight Module 2 — confirmed in proposal |
— | HIGH ✓ | MOD | — | HIGH ~ | Partial* | MVP — Aronlight |
| Discount / Price Approval Lamosa design partner track |
HIGH ✓ | MOD ~ | MOD | — | HIGH ~ | No | MVP — Lamosa |
| Escalation Logic (add-on: Naranja/Rojo path for Lamosa) | MOD | LOW | MOD | — | MOD ~ | No | Phase 2 |
| PO / Supplier Approval | MOD | MOD | HIGH ✓ | — | MOD ~ | No | Phase 2 |
| Credit / Terms Approval | MOD | HIGH | — | — | MOD ~ | No | Phase 2 |
| Returns / Credit Note | MOD | MOD | — | MOD | MOD ~ | No | Phase 3 |
| AI Copilot (Quote Building) | — | MOD ✗ | MOD | — | MOD ~ | Partial | Phase 3 |
| Voice Processing | — | — | — | — | — | Yes | Potential ~ |
* Mercura covers Inbound Request → Quote and Spec Matching but has no Odoo integration and no WhatsApp — making their product unusable for Aronlight. We are building these workflows for Aronlight directly. "Partial" = Mercura covers the concept but not for this client. ~ = guessed, no confirmed client use case yet.
Different buyer (ops/manufacturing director vs. commercial manager), different data sources (production systems, machinery logs vs. ERP/CRM), different ROI story. Keep separate from Track A.
| Workflow | Build Time | Impl. Fee (one-time) | Annual Base | What's Included (flat, unlimited use) |
|---|---|---|---|---|
| Inbound Request → Quote | 5–6 weeks | $10,000 | $12,000/yr | Unlimited requests · Odoo integration · email + WhatsApp channels · quote log in ERP |
| Spec / Product Matching | 4–5 weeks | $8,000 | $8,000/yr | Unlimited catalog queries · semantic search across full SKU catalog · Odoo catalog sync included |
| Discount / Price Approval | 3–4 weeks | $5,000 | $8,000/yr | Unlimited approvals · Verde/Ámbar/Rojo rules engine · decision log · WhatsApp/Teams/email delivery |
| Escalation Logic (add-on to Discount Approval — Naranja/Rojo escalation path) | +1–2 weeks | $2,000 | +$4,000/yr | Unlimited escalations · precedent log · decision brief generation |
| PO / Supplier Approval | 3–4 weeks | $5,000 | $6,000/yr | Unlimited PO approvals · budget check · approved supplier validation · ERP write-back |
| Credit / Terms Approval | 2–3 weeks | $4,000 | $6,000/yr | Unlimited credit requests · payment history query · aging report · ERP terms write-back |
| Returns / Credit Note | 3–4 weeks | $6,000 | $6,000/yr | Unlimited return requests · parallel quality + finance routing · credit note generation |
| AI Copilot | 6–8 weeks | $15,000 | $10,000/yr | Unlimited queries · per-seat license for all sales reps using the tool |
Implementation is quoted as a bundled package when 2+ modules are built simultaneously — bundled pricing is ~30% below per-module sum. Billed in 3 milestones: 40% at signing · 40% at staging complete · 20% at go-live. Annual subscription starts Month 2 — first month free. All annual fees billed upfront, no volume counting, no overages.
Tiers apply per module. A client using Module 1 + Module 2 pays per-module annual fees at their tier. Lamosa (Discount/Price Approval, ~1,200 approvals/month) sits in Growth.
For each MVP workflow: why each client is rated HIGH or MOD, whether the workflow is already in a proposal we sent, and what action is needed.
Subscription starts Month 2. First month on us while the team gets up to speed.
/red-team "AI Approval Middleware" — stress-test before committing
/market-scan "approval automation" "LatAm" — validate demand by geography
/evaluate-opportunity — full business case with financials