15 years of human capital research | 32+ companies served | cash-flow positive since 2022
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The Problem
Why is their growth stuck?
R&D companies. High EBITDA. Low competition.
Untouched by the disruption outside
The world shook. They didn't.
The world was disturbed by tariffs and wars. But these companies were unaffected, their R&D is too strong.
So why do they struggle to sell outside their known network?
The constraint
Their offering is very different and very technical. Existing templates and playbooks don't work.
To sell something this different and this technical, they need the world's best storyteller.
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The Solution
PDGMS is that storyteller.
It researches the company, its industry and market trends, then tells the story that sells. Storytelling is the wedge; from there PDGMS expands into the rest of their execution stack. A DT Forward Deployed Fellow runs six months of high-velocity experiments to find what works, then codifies it into the workflow below. Here: an R&D maker’s engine to win 50 client meetings this quarter.
The Fellow proves the approach that works once, codifies it, then exits. The platform runs it from then on; your team makes the calls that need a human. PDGMS fills half the sales and marketing seats to make the other half perform better. That is the wealth we create.
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Traction
We found this market from inside India's Hidden Champions
Four years running their SAP and HubSpot enrichment. We kept the relationships, grew the revenue through every pivot, and from the inside we found the market and the need for PDGMS.
Genesis · our clients pulled the platform out of us
Four years of paid, retained client work pulled a product out of us.
* A sister-concern e-commerce company ran 2022 to 2025; the AI AdTech agency, 2024 to now.
3What each one did · for reference
India's largest probiotic maker
Sales pipeline rebuilt 4 YRS
CRM
AI AdTech, AI-driven advertising
5-year skill in 1 year 4 YRS
HCD
API maker, NASA-scientist founder
Real-time, by exception 4 YRS
Plan vs Actuals
Maverick yarn maker
SAP plan-vs-actuals, for EBITDA NEW
Live
2History of pivots · revenue grew every year, bootstrapped
32+ organizations, cash-flow positive since 2022, on zero capital raised. We did not pick this market. We discovered it from within.
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The Market
A ₹325 Cr India beachhead · 1,301 R&D makers we can win
We start where we already win: ~1,301 DSIR-registered R&D makers in India, a ₹325 Cr serviceable market our storytelling wedge can reach. The same engine opens ~100,000 makers globally ($1.5B). That is the upside, not the headline.
Hidden Champions | They dominate the global supply chain
They already pay for high-quality software and services.
~3,400 · elite
~30,000-50,000 · mid-market
~100,000 · R&D-active mid-caps (the cream)
Out of scope by design
✕ 60,000 MNCs
bureaucratic, multi-year cycles
✕ 358M SMBs
price-led, high churn
TAM · GLOBAL
$1.5B
100k × ~$15K · the upside option
SAM · INDIA BEACHHEAD
₹325 Cr
1,301 makers · what we win first
SOM
₹32 Cr
~130 × ₹25L Yr-1 · India · 3-5 yrs
India entry. 1,994 DSIR-registered R&D centres; 79% under ₹1,500cr, 65% under ₹500cr (1,301 in our SAM). We earn ₹25L in Year 1 (₹10L platform + a one-time ₹15L FDE deployment), then ₹10L recurring at 75% margin; ~$15K recurring globally.
Why they compound. 3,400+ Hidden Champions, 1,300 in Germany. They grow ~10% a year, 2.5x in a decade, file 5x the patents per head of larger firms, and have minted ~200 billionaires.
Sources. Tier 1: Hermann Simon (~3,400 Hidden Champions). Tier 2: Eurostat SBS 2024 (251,000 EU medium firms), NCMM (US middle market). Tier 3: WIPO IP Indicators 2025 (patent filings), NSF BERD (R&D performers). Base: World Bank (~358M MSMEs). SAM: DSIR (1,994 firms, 65% under ₹500cr). TAM/SOM method: accounts × ACV, SOM as % of SAM (HG Insights, Pear VC). Tier 2-3 firm counts are triangulated estimates from the cited counts.
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Business Model
₹10L recurring ACV · 44% now → the 75% we already earn on HCD
Hidden Champions have the R&D the world wants, but they sell inside their known network. Our FDE studies their PMF, institutionalizes their sales engine, they mint money, we grow with them.
UNIT ECONOMICS
RECURRING ACV
₹10L
per workflow · 75% at scale
YEAR 1
₹25L
incl. one-time deployment
CAC
₹2L
at scale · ₹9L at seed
WHAT WE SELL
FDE
deploys the platform, then exits
₹5–20L / yr
20–30% gross margin
PDGMS
the recurring asset · BYOK
₹1–10L / yr
70–75% gross margin
Why ₹25L, not $1M. A formal ontology an AI can operate → reused across clients, not rebuilt → self-served on a visual flow. The platform does the work, not a person; the FDE sets it up once, then exits.
Value far above price. ₹25L is about 0.07% of a ₹375cr maker's revenue; a fraction of a percent of growth returns it many times over.
# FDE exit: FDEs exit client engagement upon workflow stabilisation, typically within 12-24 months. All tools and workflows built by the Fellow are housed within PDGMS, making PDGMS a natural continuation on a pre-agreed retainer. Clients may absorb the FDEs directly.
Margins & CAC: DeepThought internal. CAC ₹2L is marginal at scale (4 BDRs → 16/yr; ₹32L ÷ 16); seed blended CAC ~₹9L includes the one-time ₹1.5Cr brand engine (Slide 8) that compounds beyond the first cohort. Growth uplift: IDC / Gartner. Segment: Hidden Champions (Simon; Springer). Reconciles to Slide 5: 16 flagship accounts holding ₹25L ACV for 2-3 years on new projects (expansion across the execution stack) = ₹4 Cr ARR.
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Competition
Mission-critical AI, made feasible · only PDGMS is both
Palantir proved this category, AI that runs the work, is worth a fortune. Serving a ₹375 Cr maker at ₹25L was never its job. That is the maker we serve, with the same kind of execution AI, at a price they can pay.
MOAT 1 · CHANGE MANAGEMENT, FORMALIZED
Encoded change management, not an interface
Formalized from 15 years of cognition research and 32 builds, so one trained operator runs what used to take a team of engineers and change managers. Today a DT FDE; at scale, a client's own first-principles hire. The operator is interchangeable; the process is the moat.
MOAT 2 · THE ONTOLOGY + ITS COMPOUNDING CORPUS
A formal ontology an AI can finally operate
The science: a formal, computable execution ontology, a 12-stage / 74-node grid from 32 builds and 38 frameworks, academic for thirty years because only a human could operate it. An AI now can. The durability: ship it and the schema can be copied; the corpus of 32 builds compounding it cannot. Each deployment makes the next one sharper.
THE ONTOLOGY, WORKING
That ₹375 Cr maker, read from 3 discovery calls.
Founder's brief: speed up production, delivery runs 13 days against a 10-day promise.
The ontology scored 74 nodes and located the break elsewhere: no one owns improvement (node I3), no way to test a fix (I5), and the real constraint sits upstream in the order book, not on the floor.
→ Build the design layer, not a faster line.
Competitor positions: vendor AI products (Agentforce, Breeze, Now Assist) and Palantir filings (enterprise ACV). Moats: DeepThought HCD-to-FDE pipeline and a 15-year human-capital-development ontology. CRM fit: TruSummit, ARP Ideas.
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Go-to-Market
We win the first 16. The platform does the rest.
How we win a client · the 3-day Growth Bootcamp
Leadership arrives at the solution; the FDE codes the prototype live. 16 clients in 12 months.
The product runs the bootcamp · what every prospect sees in PDGMS
pdgms · their Growth Space
Growth Charter
Growth Workflows
Deliverables
Roadmap Visual
Previews
Proposal
YOUR GROWTH, AS AI WORKFLOWS
today
₹24 Cr
potential
₹32 Cr
AI Scheduling
Demand Forecasting
Shopfloor Quality
Account Intelligence
+ ₹8 Cr EBITDA · every rupee traced to a workflow
Their growth as AI workflows before they sign. The ₹375 Cr yarn maker, just won at ₹2.1L/mo platform setup, no negotiation.
Scale · who delivers as we grow
DT can do about 100 deployments itself; certified partners and self-serve take it to 100,000, using reusable ontology blocks and 15-day training
DT deploysNOW
first ~100 · deep, flagship, high-revenue
Certified agencies
DT-certified partners deploy
DT-Academy students
certified, picked from a portal
Client self-serveAT SCALE
ontology blocks · 15-day setup
In year one, our FDE does the hard part, the change management and the first build, then hands over the keys. As we build more of this into the product, each client needs us less, until a new one can run it themselves from day one.
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Team
The founder writes the core. We train the operators.
TarunFounder · mathematician, architect of the core
He owns the abstract architecture and writes the PDGMS core: the execution ontology, the 38 frameworks, the Context OS. 3 engineers complete the build and test cases from his roll-out plans; 10 interns extend it through a sandbox; he runs the whole build AI-assisted.
Mathematics & Theoretical CS · researched with Dr. Vijay Bhatkar (PARAM supercomputer) and Prof. R. Ramanujam (IMSc) · IAS & KVPY research fellow (IIT-H · IISER Pune · IMSc) · 2nd, Madhava Mathematics Olympiad (NBHM, Govt of India) · TEDx speaker.
Operators we manufacturednow embedded at clients, running ₹100–500Cr companies · proof the factory works, not our payroll
Sravan Kumar
Chief of Staff
Pharma · ₹200Cr+
Works directly with the MD, a NASA-scientist founder. Brought in AI that cut purchase-to-dispatch 3 days → 1, and runs decisions that reshape the factory floor.
BBA fresher→Chief of Staff
Shagun Mishra
AI Programs Lead
Probiotics · 60+ countries
Shipped 58 software modules as a 2023 fresher, before AI tools existed. Led a 20-member team; now runs AI Programs at the largest probiotic maker, in 60+ countries.
BTech fresher→AI Programs Lead
Jayaraj
Engagement Lead
DT client companies
Right hand to company Directors on growth strategy and execution, driving organisational transformation across manufacturing and services clients.
BTech fresher→Engagement Lead
Leadership & mentors
Gopala Krishna
President
30+ yrs SME strategy · lead consultant UNDP, World Bank, ADB, GIZ · TISS faculty.
30 yrs tech & product across SaaS, manufacturing, healthcare.
The factory5,000 apply → 25 invited → 5 hired / mo|1 FDE : 3 clients today →1 : 10+ at scale|0.1% selected · no bench · demand-gated
Build team: founder (writes the core) + 3 engineers + 10 interns on a sandbox. The three operators shown are employed by client companies, not DeepThought. They evidence the factory's output. Intake: DeepThought Fellowship (5,000 applications/mo → 25 virtual-tour invites → 5 hires). Reconciles to Slide 8 and Slide 6.
Software can be bought. A founder who writes the core, and the operators we train to run it, cannot be.
