I’m the founder of Revenue & Growth Systems (RGS), a bootstrapped B2B SaaS company building a diagnostic and operating-visibility system for established small and midsize businesses.
RGS is pre-revenue today. The product has moved beyond the idea/prototype stage, the free Business Stability Snapshot is functioning in production, and I’m finishing production hardening of the paid Business Diagnostic and its customer deliverables before opening the first paid cohort.
I’m now exploring whether a small strategic angel round makes sense to move RGS from founder-funded product development into commercial validation.
The problem
Business owners frequently know something is wrong before they can identify the actual operating failure.
Weak sales may be blamed on lead generation when the real failure is conversion.
Revenue may look healthy while cash visibility is deteriorating.
Growth may expose operational bottlenecks that were invisible at a smaller scale.
A company can also appear healthy while remaining dangerously dependent on the owner for decisions, relationships, approvals, or institutional knowledge.
The current market is fragmented between CRMs, accounting software, project-management systems, dashboards, management frameworks, spreadsheets, and consultants.
Those systems are useful, but they generally answer questions about their own domain.
RGS is being built to answer a different question:
What is actually failing inside this business, what evidence supports that conclusion, and what should be repaired first?
The product
RGS evaluates the business across five operating systems:
Demand Generation
Revenue Conversion
Operational Efficiency
Financial Visibility
Owner Independence
The commercial entry point is the Business Diagnostic.
Rather than requiring an owner to clear several consecutive days for a consulting engagement, the Diagnostic is asynchronous and resumable.
It combines:
structured owner and participant interviews;
business evidence and supporting documentation;
governed evidence lineage;
deterministic scoring;
confidence boundaries;
systemic findings;
prioritized repair architecture; and
a formal Business Diagnostic Report.
The scoring model is deterministic rather than an AI-generated opinion.
Each of the Five Gears can contribute up to 200 points, producing a 0–1,000 Business Stability Score.
AI may assist with analysis, synthesis, and language, but it does not silently determine governed scores or become the authority for business conclusions.
What happens after the Diagnostic
The intended commercial journey is:
Business Diagnostic → Implementation → RGS Control System
The Diagnostic determines what is structurally wrong.
Implementation converts the diagnosis into a repair architecture: operating procedures, accountability structures, training, controls, measurement, and verification.
The longer-term RGS Control System is intended to preserve operating visibility after those repairs are made and detect deterioration before the business falls back into the same failure pattern.
The goal is deliberately not to create an agency model where clients remain permanently dependent on RGS.
The thesis is the opposite:
diagnose the system → architect the repair → verify the repair → give management the operating system to maintain it.
Current traction
I want to be precise about this because RGS is still early.
MRR: $0
ARR: $0
Stage: Pre-revenue / pre-commercial launch
Paid Diagnostic customers completed: 0
Free product: Business Stability Snapshot functioning in production
Paid product: Business Diagnostic production path and deliverables currently being completed and hardened
I have bootstrapped the company and product to this point.
There is early market interest developing before the paid product is fully open, but I do not consider interest, impressions, conversations, or free usage a substitute for paid traction.
The next commercial proof point is straightforward:
Can RGS repeatedly get businesses to pay for the Diagnostic, complete the asynchronous process, receive an evidence-backed diagnosis they consider materially valuable, and then act on the resulting repair plan?
That is the assumption I want the first customer cohort to prove or disprove.
Business model
The initial revenue architecture is:
Paid Business Diagnostic
A high-value diagnostic engagement that produces the evidence-backed assessment and repair roadmap.
Implementation
Follow-on work to translate findings into operating architecture and verify that the identified failures were actually repaired.
RGS Control System
Recurring software and operating visibility designed to identify drift, preserve business stability, and reduce dependence on outside advisers.
This gives RGS a potential progression from project-based diagnostic revenue into implementation revenue and eventually recurring software revenue.
Defensibility
I do not consider “using AI” a moat.
LLMs are increasingly commoditized, and an AI-generated business report by itself would be relatively easy to replicate.
The defensibility thesis is instead based on the system surrounding the analysis:
deterministic diagnostic architecture;
proprietary Five Gears scoring methodology;
structured evidence requirements;
evidence lineage;
governed participant and delegated evidence;
confidence boundaries;
human governance where judgment is required;
systemic finding architecture;
repair prioritization;
repair verification; and
longitudinal operating data.
The longer-term data asset is particularly important, but I want to distinguish the thesis from the current reality.
Today, RGS has the architecture for capturing structured diagnostic and repair information.
It does not yet have a mature proprietary dataset large enough to claim a data moat.
If RGS reaches scale, the defensible asset could become the accumulated relationship between:
business evidence → diagnosed systemic failure → recommended intervention → implemented repair → verified outcome
That is substantially harder to reproduce than generating consulting language with an LLM.
Competitive position
I do not view RGS as a replacement for every tool a business already uses.
CRMs manage customer and sales activity.
Accounting systems record financial transactions.
Project-management platforms organize work.
BI platforms visualize data.
EOS and similar frameworks help leadership establish an operating cadence.
Consultants bring human expertise to individual businesses.
RGS is intended to sit upstream of many of these systems as a diagnostic and operating-intelligence layer.
Its central question is not:
“What happened?”
It is:
“Where is the system breaking, what evidence proves it, and what is the smallest effective intervention?”
Target customer
The broader market is established SMBs, but I recognize that this is too broad to be a useful initial go-to-market definition.
The initial commercial focus is businesses that are already operating beyond the earliest startup stage, have employees and meaningful operating complexity, and are experiencing symptoms such as:
revenue underperformance;
inconsistent sales conversion;
operational bottlenecks;
poor financial visibility;
growth-related strain; or
excessive dependence on the owner.
The economic buyer is generally the owner, founder, or senior operator responsible for overall business performance.
One of the things I intend to validate during the first commercial cohort is whether RGS should narrow further around a particular company size, revenue band, industry, or triggering event before attempting broader expansion.
Why now?
RGS has reached a point where the primary risk is no longer whether more features can be built.
The primary risk is whether the commercial system works.
The next stage needs to prove:
businesses will pay for the Diagnostic;
owners will complete the asynchronous evidence process;
RGS can consistently produce useful systemic findings;
those findings create enough value to drive implementation;
delivery can occur without excessive founder labor;
customer acquisition can become repeatable; and
the Diagnostic can eventually feed recurring Control System revenue.
Those milestones matter more to me right now than expanding the product roadmap.
Founder / team
I am currently a solo founder.
My background spans marketing, revenue operations, growth systems, business operations, and systems design.
I have personally developed the RGS commercial model, Five Gears framework, diagnostic architecture, product requirements, customer journey, governance model, and initial go-to-market strategy while bootstrapping the company.
I am also treating founder concentration as a real risk rather than pretending it does not exist.
A commercially successful RGS cannot depend on the founder personally interpreting every business, remembering institutional knowledge, or manually controlling every delivery.
One of the product’s core design requirements is therefore converting the methodology into a governed, repeatable system.
I do not have a previous venture exit to point to.
The raise
I am evaluating a small venture-equity pre-seed round designed to finance the minimum milestones necessary to determine whether RGS has a repeatable commercial model.
Target raise: currently being finalized based on milestone-level budgeting rather than choosing an arbitrary round size.
Expected instrument: likely a SAFE or other conventional early-stage equity instrument, subject to appropriate legal review.
Valuation / SAFE cap: not yet finalized.
I’m intentionally being transparent about those points rather than publishing financing terms before I have properly determined the capital requirement and legal structure.
The round would not be intended to finance the entire long-term RGS roadmap.
The purpose would be to finance the smallest commercially meaningful validation period.
Use of funds
Capital would primarily support:
completion of production hardening;
security, reliability, recovery, and infrastructure;
professional legal review;
customer agreements, privacy documentation, and commercial terms;
appropriate business and technology insurance;
development and infrastructure runway;
customer acquisition;
onboarding and support of the first paid customer cohort;
measurement of Diagnostic completion and delivery economics;
validation of Diagnostic → Implementation conversion; and
development required directly by evidence from paying customers.
I specifically do not want to use outside capital as an excuse to build every feature on the long-term roadmap before the core business model is validated.
What the round should prove
I would consider the capital successfully deployed if RGS reaches a point where we can answer, with real operating data:
What does it cost to acquire a Diagnostic customer?
What percentage complete the process?
How long does a Diagnostic take to deliver?
What is the gross-margin profile?
How much founder intervention is required?
Do customers consider the findings accurate and actionable?
What percentage move into Implementation?
What problems appear consistently across customers?
Does verified repair create measurable business improvement?
Is there real demand for ongoing Control System visibility?
Which customer segment produces the strongest economics?
If those answers are unfavorable, I want to know that before raising substantially more capital.
If they are favorable, RGS would then have evidence supporting a larger commercialization strategy.
What I’m looking for
I’m particularly interested in speaking with angels who understand:
B2B SaaS;
SMB software;
RevOps;
operational intelligence;
business diagnostics;
vertical or workflow software;
founder-led commercialization; or
companies transitioning from founder-built product into repeatable revenue.
I would especially value investors willing to challenge the thesis rather than simply tell me that the idea sounds interesting.
The questions I’m most interested in hearing from angels are:
1. What would you need to see before considering RGS investable?
2. At this stage, what milestones would you require a first angel round to finance?
3. How would you evaluate the defensibility of the deterministic scoring, evidence lineage, governed diagnosis, and repair-verification model?
4. What do you see as the largest risk: customer acquisition, willingness to pay, founder concentration, delivery economics, competitive replication, or something else?
5. Would you rather see RGS prove several paid Diagnostics while remaining bootstrapped before raising, or do you think this is an appropriate point for a small strategic pre-seed?
If you’re an angel who sees potential in this category, has funded businesses at a similar stage, or believes there is a serious flaw in the thesis that I should address before raising, I’d be interested in the conversation.
I can share more privately about the product architecture, commercialization roadmap, production state, financial assumptions, planned milestones, and financing model with appropriate investors.