Confidential Proposal
SMAPE SRL · Confidential
Six months. One operating system that measures everything you run, takes field personnel and equipment out of Excel, makes business development predictable, and captures 36 years of senior-engineer know-how — built to absorb the +76% expansion into Middle East, West Africa, and LATAM without proportional hiring.
Built from the 28 May discovery call, the three pains and three opportunities you sent in writing, and the 10 June working session — the KPI tree, the two customer tiers, and the M&A strategy are all reflected here.
▶ Explore the live OS demobuilt from your own planning spreadsheets · IT / EN / RUBuilt from the 28 May discovery call — then restructured around the three operational pains and three opportunities you sent us in writing. Nothing here was invented for you to react to. It's your list, made executable.
The Data & Recommendation Engine. Your words: "an algorithm that collects all the data we measure during the operations, analyses them, identifies patterns and ultimately provides insights, suggestions, job modelling that help us provide a better service and can monetize as well." The data your equipment already collects inside the well becomes a second revenue line — and 5–20 patentable methods. Integrated into the build, or added later as a standalone project. Detailed in section "Data Engine" below.
The M&A Engine. Data-driven sourcing across all three lanes of your strategy — horizontal (operators like you, in the geographies you're targeting), vertical (the consultancy businesses that sell integrated packages and become a distribution channel), and supply-side (equipment manufacturers). Continuous scanning, structured target dossiers, a managed roll-up pipeline. And the integration multiplier: every company you acquire gets the OS on day one — out of their spreadsheets, into your visibility, running your playbook from week one. Included in the core engagement as a leadership-level module. Delivered in Phase 3.
After the discovery call, you sent the three toughest operational pains and three opportunities in writing. Here is each one, verbatim — and where it lives in this plan.
| Your opportunity | Where it lives in this plan |
|---|---|
| 1 · Agentic scanner for projects, tenders & spot jobs — "continuously scan all internet (news, socials, official tendering platforms) to find upcoming projects, tenders, spot jobs and filter those opportunities" | Opportunity & Tender Radar — Phase 2, core engagement. Feeds the Sales Engine directly. |
| 2 · Agentic scanner for M&A targets — "continuously scan all internet to find companies and business that can be a good fit according to our M&A strategy and goals" | M&A Engine — Phase 3, leadership-level module covering all three lanes you described: horizontal operators, vertical consultancies, supply-side manufacturers. Included in the core engagement. |
| 3 · Operations data algorithm — "collects all the data we measure during the operations, analyse them, identify patterns and ultimately provides insights, suggestions, job modelling… and can monetize as well" | Track 4 — The Data & Recommendation Engine. Integrated into the Full Build, or added later. The decision now on the table. |
Pain #1 is unsolvable while Pain #2 lives in Excel. You cannot measure what isn't captured — and a spreadsheet captures keystrokes, not operations. The personnel & equipment system isn't just replacing spreadsheets; it is the data-collection layer your KPI system requires. One build solves both pains — by design, not by coincidence.
As you noted on the call: the back-office workflows — HR, accounting, procurement — weren't listed only because they're not the main pain and are easier to automate. Agreed on both counts. They're in scope across Phases 1–3.
You sent us four screenshots as examples — and we know they're exactly that: a starting point, not the full list. We recognize every one of them — heroic work, maintained by hand, holding up a €-million operation. Here's what each becomes inside the OS — and you don't have to imagine it: open the live demo and click through all four, in Italian, English, or Russian.
These four sheets are maintained by some of your most senior operational people. Every hour they spend coloring cells is an hour not spent on the work only they can do. The OS gives those hours back — and turns the planning data they were already creating into the measurement layer the whole company is missing.
There are more spreadsheets where these came from — there always are. Discovery maps the full Excel landscape across all 8 entities. These four go first because they run your two revenue-generating assets; every sheet after them lands faster, because the data spine, the patterns, and the habits already exist. The goal isn't replacing four spreadsheets — it's that no operational process lives in Excel by the end of the build.
The written top-3 sharpened the priorities. The discovery call set the foundations — these are the live priorities you named in the room, and they still anchor the plan.
"It takes at least two years for full training as an operator. In the last two years we hired 10+ junior people with no experience. We're doing intensive massive training to accelerate. About 20% of training is theoretical, 80% is on-the-job. We formalized the skill matrix for the first time this year. We don't track certifications in a system yet — we're starting now."
This is one of the highest-leverage things to fix in the OS. Every month of ramp time compressed is a month of productive field capacity earned — and the bottleneck you called the #1 expansion blocker starts to ease.
You raised the senior-workforce digital-lag concern on the call. The answer isn't a chat-with-AI experience — that would meet resistance. The answer is that the AI disappears into the workflow, the way saving a Word file as PDF "uses" software no one thinks about.
"Nobody in your company is resistant to Microsoft Word or Excel. Nobody is resistant to SAP. They're not resistant to digital tools. They would be resistant to a chat-AI experience — but that's not what we're building. We're capturing their workflow in an interface that fits their workflow. The awareness of AI is minimal. Like when they save a Word file as a PDF — they don't care about the algorithm. They just know the PDF is there."
That's why this lands with a senior, operationally-oriented workforce. You're not asking them to learn AI. You're asking them to work the way they already work — just much faster, much cleaner, and in one place instead of six.
Lead with your pain #1: you cannot improve what you don't measure. Phase 1 builds the operations data spine that makes measurement automatic, puts the first live KPIs in front of leadership, and starts capturing the know-how that's the gate on continuity — with recruiting and training running on the same people-data spine.
| Agent / Module | What It Does | Impact |
|---|---|---|
| Mission Control — The KPI Tree | Your financial KPIs (where you're already strong) broken down into a tree of operative KPIs: fleet utilization, crew utilization, unplanned downtime, non-conformity trends, certification coverage, tender conversion. Each department sees its own level — and how it rolls up to the company P&L. KPIs collect themselves from work done inside the OS. | Your pain #1, answered — as the breakdown-tree you described. "We cannot improve what we don't measure" stops being true in month 2. |
| Operations Data Spine | The single data model under personnel, equipment, jobs, and certifications. Your four planning spreadsheets re-modeled as live, connected records — the foundation the Phase 2 scheduling boards run on. | Your pain #2 starts here. Every later module — and every KPI — stands on this spine. |
| Recruiting Pipeline Agent | Job description automation, multi-channel sourcing, candidate screening, interview scheduling, offer drafts. Tracks pipeline health by role / region. | Directly addresses the bottleneck you named on the call. Hire-to-offer cycle measurably shorter. |
| Training & Certification OS | The skill matrix you formalized this year becomes a live system: theoretical micro-modules, supervisor-led on-the-job evaluations, per-role certification ladders (CT Operator → Chief Operator → Supervisor), per-crew status dashboards. | The 2-year operator ramp materially compressed. Every supervisor evaluation is captured, not lost. |
| Mentor-Assist Agent | On-the-job training co-pilot for supervisors: structured evaluation forms, AI-summarized field feedback, gap detection per junior operator. | The 80% on-the-job part of training becomes measurable and consistent across crews. |
| Knowledge Capture Agent | Structured interviews with senior engineers + post-job analyses + ISO manuals + SOPs ingested into a searchable, agent-queryable brain. | 36 years of know-how stops depending on who's in the room. Highest-risk asset deterioration arrested. |
| QHSE Audit Prep Agent | Continuous monitoring against ISO 9001 / 14001 / 45001 / 14064-1. Flags non-conformities before audits find them. | Protects the A1 Cribis D&B rating. Protects the Top 100 ESG award. |
| Multi-Entity Document Vault | ISO 27001-ready unified storage across all 8 entities. Replaces the OneDrive stand-by; resolves the physical-server dependency. | Closes the in-flight ISO 27001 project at lower total cost. |
Leadership sees live operational KPIs for the first time. The personnel + equipment data spine is live and loaded from your four spreadsheets. The recruiting pipeline runs in the OS, the skill matrix is tracked per person and per crew, and the top 12–15 senior engineers are being interviewed into the Brain. Document Vault is ISO 27001-ready.
Where the P&L savings show up. The four spreadsheets you sent — operations planning, field personnel planning, equipment non-conformities, equipment planning — formally replaced inside the OS. CRESCO dismissed. The in-flight custom operations software absorbed. And your pain #3: the BD/sales process becomes a managed, measured pipeline.
| Agent / Module | What It Does | Impact |
|---|---|---|
| OS Equipment Hub (CRESCO replacement) | Full equipment registry, certificates, manuals, maintenance, fatigue tracking — integrated with Vista IoT telemetry. | CRESCO dismissed. Field operators query equipment status from anywhere. |
| Operations Scheduling Boards (absorbs in-flight NOV-based project) | Personnel planning · equipment allocation · maintenance schedules — the four spreadsheets you sent, live on the Phase 1 data spine. Conflict detection, certification & medical-visit awareness, rotation-rule limits, double-booking prevention — at planning time, not on site. | Your pain #2, closed. The "lot of confusion in operating processes" you named, eliminated. Custom-software project absorbed at lower total cost. |
| CT Fatigue Tracker | Continuous CT string fatigue monitoring across the fleet (augments Achilles). Predicts string replacement windows. | Avoid in-job failures. Optimize string utilization. |
| Real-Time Job Monitor | 24/7/365 control-room agent watching every live job across all geographies. Alerts on anomalies, hands off to the on-call engineer with full context. | Your "Remote Support Worldwide" becomes intelligent, not reactive. |
| Maintenance Predictor | Predictive maintenance from IoT sensor data + 36 years of job history. | Equipment uptime up; emergency mobilization down. |
| Service Design Agent | Reads well data + customer constraints + 36 years of similar interventions → produces job design, CT string spec, BHA spec, treatment recommendation. | 2–3 senior engineers × days → hours, with full traceability. |
| Opportunity & Tender Radar (your opportunity #1) | Continuously scans news, socials, and official tendering platforms across all 6 regions for upcoming projects, tenders, and spot jobs — filters to what SMAPE can win, and auto-drafts technical + economic responses from your won-tender library. | More leads in the pipeline, and 2–3× more tender responses with the same BD team. |
| Sales Pipeline & BD Process | Every opportunity tracked from first signal to signed contract, in two lanes: Tier 1 framework agreements (prequalification status, tender cycles, the five-year windows per country) and Tier 2 spot jobs (leads, conversion per stage, the consultant / referral channel made systematic). Account history from the Brain. | Your pain #3, closed. Sales stops depending on memory and becomes a managed, measured process — more leads, higher conversion, and the ~10% offer win rate finally measurable and improvable per stage. |
| Prequalification Dossier Builder | Tier 1 prequalification means proving technical capability: equipment, people, certifications, track record. The OS already holds all of it — equipment registry, certification matrix, 36 years of job history. The dossier assembles itself per customer requirements, kept current continuously. | The months-to-years prequalification stage compressed — and SMAPE stays permanently prequalification-ready for every NOC / IOC bidding list it targets. |
| Crew & Expat Deployment | Optimizes crew scheduling across 8 entities, including the 8 planned expats (2 per area). Handles visa, tax, and regulatory constraints per country. | Critical for the +53 local FTE in CIS / WA / ME / LATAM. |
The four planning spreadsheets replaced inside the OS — and the next wave of spreadsheets (mapped in Phase 1 discovery) scoped and landing on the same spine. CRESCO formally dismissed. The custom NOV-based operations software project absorbed. The sales pipeline live with the Opportunity & Tender Radar feeding it. Real-time job monitoring live. SAP dismissal decision finalized — keep, partial, or full replacement.
This is where SMAPE goes from "using AI tools" to "owning intelligence." The compound intelligence gets smarter with every job. No competitor in oilfield services can replicate it — they don't have your 36 years of data.
| Asset | What It Does |
|---|---|
| Well Intervention Memory | Trained on 36 years of CT, Nitrogen, Pumping, and Stimulation jobs. Predicts intervention outcomes by similarity. No oilfield-services competitor can replicate this. |
| Chemical Recipe Brain | Your lab's complete formulation history made queryable. Treatment recommendations grounded in your own success / failure record across decades. |
| Client Relationship Memory | Every major-account interaction across Europe / CIS / North Africa / Middle East — preferences, contracting patterns, technical preferences. White-glove key-account management at scale. |
| M&A Engine (your opportunity #2) | Data-driven target sourcing across your three lanes — horizontal operators in target geographies, vertical consultancies, supply-side manufacturers. Unstructured signals (news, registries, social, press) normalized into structured target dossiers: financials, footprint, capability fit, owner profile. A managed roll-up pipeline with screening criteria and deal stages — so the first acquisition SMAPE ever runs is run with a system. |
The OS and The Brain turn SMAPE from a pure services company into a services-plus-platform company. The intelligence is owned. If SMAPE ever runs a strategic-partner, IPO, or exit process, owned proprietary intelligence is a multiple expander, not a line item — and if Track 4 (the Data Engine, below) is engaged, the patentable methods compound that further.
And for the M&A strategy specifically: the OS is the integration platform. Every acquired company — operator, consultancy, or manufacturer — gets onboarded into the OS on day one: their personnel, equipment, and pipeline visible in the same Mission Control, running the same playbook. That's the difference between buying companies and building a group.
Integrated into the Full Build — or added later as a standalone project. Your equipment already collects pressure, temperature, and flow data inside the well via the NOV data acquisition system. Today, that data is captured. Tomorrow, it becomes the source of a second revenue line and a defensible IP portfolio.
"We have hardware to collect a lot of data during operations from the well. Pressure, temperature, flow. Imagine software that collects all this data, understands it, identifies patterns. Number one, this is already a value. Number two, we can use these patterns as input for our own intervention design. Number three, this can become a data-driven service we sell to clients."
Today, a technical engineer looks at well data, talks to the customer, thinks about it, recommends a solution, then talks to commercial — who packages an upsell. The Data Engine collapses that loop into a recommendation engine grounded in pattern analysis across every well SMAPE has ever serviced.
| Module | What It Does |
|---|---|
| NOV Data Ingestion | Pulls every job's pressure / temperature / flow telemetry from the NOV data acquisition system into a unified time-series store. The foundation. |
| Pattern & Anomaly Engine | Machine-learning models — not LLMs — that identify well-condition patterns, anomalies, and intervention-success correlates across your 36 years of jobs and the live data fleet. |
| Intervention Recommender | For every well, recommends interventions (CT operation, treatment, stimulation) calibrated for revenue, cost, or risk profile — based on similar well outcomes in your own history. |
| Commercial Package Generator | Wraps each recommendation into a commercial offer: tools needed, people, methods, pricing, contract fit. The bridge between engineering insight and revenue capture. |
| Client-Tier Service Modes | Three deployment modes — Majors (Shell / BP / Chevron), NOCs (national oil companies), Small Players. Different know-how levels, different packaging, different price points. |
| Patent Method Capture | Targets 5–20 patentable methods, the first 5–10 scoped during the 9-month track. Masterkey has IP partnerships in Europe, the US, and Asia. Patents become an asset on the balance sheet and a moat against new entrants. |
The data is already being collected. The hardware exists. The 36 years of historical job context is yours. The ML models need 6–9 months of training and validation before they're commercially deployable — and that clock is calendar-bound, not money-bound. Integrated, it starts on day one and finishes inside the build. As a later add-on, it starts after delivery — the second revenue line lands roughly a year later, and costs €120K more.
The expansion-hire deferral alone covers the engagement nearly twice over. Everything else is upside.
| Value Driver | Annual Impact (Year 1) |
|---|---|
| Expansion-hire deferral — 15 of +77 planned FTE absorbed through OS leverage (loaded EU cost ~€96K/FTE) | €1,400,000 |
| Faster recruiting + faster ramp — the bottleneck you named; 6+ months of productive field-capacity earned per junior operator class | €600,000 – €1,200,000 |
| Tender velocity — 2× response capacity; one incremental win at typical project margin | €500,000 – €2,000,000 |
| SAP-related savings — if SAP is dismissed, ~€20K/yr maintenance + 30 license reductions + Excel-process automation savings | €100,000 – €300,000 |
| CT fatigue prediction + maintenance optimization — avoid in-job failures, optimize string utilization | €200,000 – €600,000 |
| Stack rationalization — CRESCO dismissed, custom ops project absorbed, OneDrive consolidated | €100,000 – €200,000 |
| QHSE / ESG incident prevention — one major audit finding avoided protects A1 rating + Top 100 ESG | €100,000 – €500,000 |
| Senior-engineer knowledge retention — avoid 1–2 critical-knowledge departures stalling projects | €200,000 – €500,000 |
| Conservative Total — Year 1 (core engagement) | €3,200,000 – €6,700,000 |
| Track 4 · Data Engine — second revenue line + patent IP (year 2+, conservative ramp) | €500,000 – €3,000,000+ |
SMAPE's 2027 plan = +77 FTE to enter Middle East, West Africa, LATAM. If the OS lets the same expansion happen with 40 fewer net hires by year three, that's a compounding annual save of ~€3.8M from year 3 onward — plus three new continents serviced without organizational stress.
Locked in during Month 1 Discovery. SMAPE's own slide 5 already mapped the direction — the OS lands that direction at lower total cost than running CRESCO replacement, ISO 27001 migration, and AI-tool rollout as three separate projects.
SMAPE's motto has always been the senior engineers in the room. The Brain captures it — every job, every recipe, every fatigue trace, every key-account playbook — so the motto holds even when the people change.
The 36 years of accumulated expertise didn't show up overnight, and it won't survive a few key retirements unless it's captured. Phase 1 prioritizes Knowledge Capture for exactly this reason. Every month delayed is exposure. Every month invested is durable institutional memory.
Mapped directly from SMAPE's org chart and value chain. Each department gets its own dashboard, its own agents, and its own slice of the Brain — while everyone works inside the same OS.
Mapped from SMAPE's stated org structure: BizDev · QHSE · HR · Accounting & Finance · Procurement & Logistics · QA/QC · Operations Manager (W/E areas) · Engineering & Technology Manager.
Includes ongoing platform updates, new agent capabilities, security patches, and the methodology improvements as Masterkey evolves. The OS stays current — it's not a one-time build that goes stale.
Token usage runs on SMAPE's own API accounts (estimated €3,000–€12,000/month at scale, depending on volume). Specific tier locks in during the final 30 days of the build via addendum.
No vendor lock-in. No platform held hostage. As part of the engagement, we define the role specs, conduct technical interviews, and onboard a small in-house team that owns the OS roadmap after the build.
By the time the engagement closes, SMAPE's team can extend the platform independently. Architecture, runbooks, agent training procedures, and the post-engagement roadmap are all transferred. Ongoing Fractional CTO support is available as a separate retainer if needed.
Clean, simple, no ambiguity. SMAPE owns everything built specifically for SMAPE. Masterkey owns the underlying platform engine and methodology.
| Asset | Owner |
|---|---|
| SMAPE OS (the custom instance — all interfaces, dashboards, workflows) | SMAPE SRL |
| The Brain (knowledge, context, memory layers — SMAPE's data) | SMAPE SRL |
| All deployed agents and configurations | SMAPE SRL |
| OS Equipment Hub (CRESCO successor / CT SAM landing) | SMAPE SRL |
| Platform engine, agent runtime, methodology | Masterkey |
SMAPE receives a perpetual, royalty-free license to use any Masterkey platform IP incorporated into the Custom Work Product, governed by the MSA.
The recommended path is the Full Build — €1,050,000 over 9 months: the complete OS plus the Data & Recommendation Engine as one program. The core OS alone is €720,000 over 6 months, with the Data Engine available later as a standalone add-on at €450,000. Net 15 on all invoices. AI token costs run through SMAPE's own API accounts during build — small (€500–2K/month), establishes the principle that token costs are an operating expense.
| Path | What You Get | Duration | Investment |
|---|---|---|---|
| The Full Build (recommended) | Complete OS (all 3 phases) + full Data Engine: models trained & validated, 5–10 patent methods scoped, first commercial pilot live — one program, one team, one timeline | 9 months | €1,050,000 |
| Core OS | Complete OS (all 3 phases) — Mission Control, the data spine, the four spreadsheets replaced, sales engine, M&A radar, the Brain | 6 months | €720,000 |
| Core OS + Data Engine later | Core OS now; Data Engine as a standalone project afterward — same scope, but the ML training clock starts a year later and the project can't share the build team on site | 6 + 9 months | €1,170,000 (€720K + €450K) |
Same Data Engine, two prices: +€330K integrated, €450K later. Deciding now saves €120K — and starts the second revenue line a year earlier, because the model-training clock starts on day one instead of after delivery.
Full Build schedule shown (3 × €350K). Core-OS-only path: 3 × €240K at signing / month 3 / month 6. The post-engagement platform subscription (see "Post-Engagement Platform") begins when the build completes.
Travel to Italy or any region as required, expensed at cost · all itemized.
Month one discovery will tell us exactly how long each integration takes — some tools will be replaced, others bridged. What's guaranteed: by month six, the team is working inside the OS, and the OS is working for the business.
AI upskilling for the people who work in the OS — office, planning, BD, QHSE, finance, and leadership (~50 users), in IT / EN / RU. Biweekly hot seats. Change champions program. Field crews aren't asked to change how they work — the OS works for them through the planners and supervisors. Fractional CTO advisory on the in-flight CT SAM, ISO 27001, and Industry 5.0 projects — so the OS becomes the connective tissue across all transformation initiatives, not a parallel project.
You sent the planning spreadsheets and the written top-3 pains and opportunities, and we went deep on all of it together on the 10 June call — the KPI tree, the two customer tiers, the M&A strategy. This proposal reflects every piece of it. Three decisions and a signature stand between here and month one.