Architect. Builder. Operator.
Most founders hit a moment where every technical decision routes back to them and there’s no one senior enough to take it off their plate. That’s the only problem Deepak solves, and he’s been solving it across three continents for ten years.
Six countries. Twenty-plus production systems. Every one owner-operated: architected, built, shipped, and handed over.
From blockchain payment rails to government edtech to a consumer platform at 1.5M+ users, the technical problem changes. The operating problem never does.
Deepak started as an engineer in a startup doing what Zepto and Blinkit do today, and watched founders lose companies not because the product was wrong, but because the right technical person wasn’t in the room when the critical decisions were made. Wrong hires. Wrong architecture. Wrong direction chosen at the wrong moment.
He quit, started building independently, and founded Frecher Hinakins, a bootstrapped technical practice that grew to 30+ clients across six countries without external funding. Through those engagements he operated at every level: architect, consultant, team builder, compliance owner, investor narrative writer.
Then came the engagement that defined the practice: being brought in as Consultant CTO to build India’s first friendship app from a blank repository, scaling it across India and the US, building the engineering team, owning security and compliance across country and state-level requirements, and delivering the technical narrative for investors. Everything a technical co-founder actually owns.
A founder’s technical problem is rarely the thing they describe. It’s almost always the decision-making structure that produced it, and that’s what gets fixed.
Every system failure is downstream of a decision that looked fine at the time. Four observations that define the pattern.
The structural move
Most early-stage teams treat infrastructure as something to fix once they have traction. By then, the decision is already made. It's just made badly. The architectural choices that look like engineering preferences at day one become migration costs, downtime events, and scaling blockers by month six. The founders who avoid this aren't more patient. They're more deliberate about which corners can be cut and which ones compound.
Produced
1.5M+ users on architecture designed, not retrofitted.
The structural move
Security doesn't layer onto an existing architecture cleanly. It has to be a design property, which means the CISO perspective needs to be in the room when the system is being drawn, not when it's being audited. GDPR, SOC 2, ISO 27001, RBI data localisation: the cost of retrofitting compliance into a running system is between 3x and 10x the cost of designing for it upfront. The founders who understand this stop treating compliance as a checkbox and start treating it as an infrastructure decision.
Produced
30+ engagements across regulated markets.
The structural move
The question isn't whether to integrate AI. It's what the surrounding system needs to look like for AI to be safe to use. Failure modes, remediation ownership, cost of a wrong output: these aren't product questions. They're infrastructure questions. The founders who answer them before shipping have a feature. The ones who don't have an incident waiting to happen.
Produced
AI shipped with defined failure boundaries.
The structural move
Cloud cost spirals aren't accidents. They're the consequence of product decisions made without visibility into the infrastructure layer: storage strategy, caching, query design, vendor lock-in. A 40% reduction in infra cost doesn't come from a procurement negotiation. It comes from rebuilding the parts of the product that were designed without cost as a constraint. The CTO who has been through this knows which architectural choices are reversible and which ones compound.
Produced
Same output at ten people as at thirty.
These are the situations founders bring to Deepak. Each has a defined outcome. None are solved by more engineers.
Ten years of delivery across the complete technology function, not advisory across it. The distinction matters.
Systems designed to hold the weight of what comes next
Infrastructure cost as a product and engineering decision
Security as an architectural property, not a layer
Full-stack delivery: mobile, web, CRM, integrations
AI infrastructure built for operational safety, not demos
Technical org design, from first hire to structured function
Not what was delivered. The state of the company before, the decisions made, and what was different after.
The situation
Engineering needed senior direction immediately, not after a 3-month search and 3-month onboarding. Every day without architectural oversight was a day of feature decisions made without context. In a consumer social platform, bad architecture decisions in this phase compound into retention problems 12 months later.
What was owned
Full product architecture. AI proximity and interest matching engine, the core product differentiator. Multi-tier subscription infrastructure across Google Play and App Store. Engineering team: hiring criteria, interview design, onboarding, culture. Sprint cadence, technical review, release discipline. Security and compliance across India, USA, and Singapore. Investor technical narrative.
How it operated
Not advisory. Every decision above required ownership, not input. The compliance architecture that keeps the platform live across India and the US was built before a problem surfaced, not after. A fractional CTO in this role costs a fraction of a permanent hire and produces the same operating output, because the operating principles are the same regardless of engagement structure.
The situation
Germany's largest independent car rental network, 15 stations, was making pricing decisions manually. A team member checking competitor sites, noting rates, updating branches one by one. In a market where competitor pricing moves daily and fleet utilisation changes hourly, revenue left on the table every day. The problem wasn't the platform. It was that the platform had no intelligence layer.
What was built
Automated competitor intelligence: daily rate ingestion from Sixt and Check24 across all vehicle classes and locations. Fleet utilisation data ingestion weighted against actual occupancy signals. Degression logic engine: yield × base rate × degression table, Starcar's exact revenue model, codified. The system turned a manual, slow process into a decision engine that directly influenced pricing outcomes across the network.
The operating principle
Revenue operations problems are almost always disguised as technology gaps. The decision to build a data processing layer rather than replace the enterprise platform saved Starcar a seven-figure procurement spend. The right diagnosis of the actual problem is the primary value a fractional CTO delivers, before a line of code is written.
The situation
Building for the Maharashtra SSC Board is not the same problem as building for urban EdTech. The user, a Marathi-medium student in semi-urban or rural Maharashtra, has fundamentally different network conditions, device specifications, and content consumption patterns. Most EdTech platforms are built for the user teams imagine, not the user who actually exists.
What was built
Student app: full SSC Board curriculum grades 1–10, Marathi medium, video/audio/notes/e-books optimised for low-bandwidth conditions. Admin panel (ReactJS): content management for curriculum administrators. Reporting panel (Angular): usage analytics, student progress, teacher performance. Subscription and access control aligned to board curriculum structure. Concurrent examination infrastructure designed for simultaneous mass test-taking.
The operating principle
Examination infrastructure fails differently from content delivery. A timed exam has three distinct load spikes: start, mid-exam, submission, each with different failure modes. Getting this right required designing the examination flow before designing the infrastructure. The architecture that came out of that process was not the simplest one. It was the one that worked correctly under real conditions.
The situation
NDIS service providers in Australia operate under strict regulatory requirements: participant data handling, audit trails, funding claim documentation. The compliance burden prevents most small providers from scaling because the administrative overhead grows with each client. The problem was not a compliance gap. It was a compliance architecture gap.
What was built
A healthcare SaaS platform purpose-built for NDIS compliance: participant management, care plan documentation, shift notes and incident reporting, funding claim generation aligned to NDIS price guides, and audit-ready record architecture. Compliance built into the data model from the first session, not retrofitted before the regulatory review.
The operating principle
In regulated industries, the cost of retrofitting compliance into a running system is between 3× and 10× the cost of building it in upfront. The CTO who has been through the retrofit knows exactly what “we'll handle compliance later” actually costs: in time, in re-architecture, and in regulatory exposure during the gap.
The situation
Project Hydro was an open-source blockchain ecosystem incubated by Hydrogen: KPMG Fintech Startup of the Year, Fast Company World-Changing Technology. A 10,000-member global developer community across 150 countries depended on the infrastructure being architected correctly. In financial infrastructure, an architecture error is not a bug to be patched. It is a security vulnerability with real financial consequences for real users.
What was built
Snowflake Topup Wallet: RESTful API generating and monitoring Ethereum wallets per ERC-1484 Snowflake identity standard. Meta-Transaction Queuing Server: off-chain queue enabling gas-free user experience. OMG Plasma Bridge: smart contract bridging Snowflake identity for near-instant low-cost transfers. KYC compliance layer: Fiat-to-Hydro and Hydro-to-Fiat remittance with full Pseudo-MSB regulatory compliance. Crosspay (London): frontend architecture for a live global money transfer platform.
The operating principle
Financial infrastructure must be correct in ways that most software doesn't need to be. A gas optimisation error costs users real money. A KYC compliance gap creates regulatory exposure. Operating at this level requires understanding the business and regulatory constraints as deeply as the technical ones, because in fintech, the two are inseparable.
Not a list of roles. Each stop is defined by the observation it produced.
India · Singapore · USA · Australia · Canada
Built production systems across six countries while completing B.Tech, leading a distributed team of 10 developers across blockchain, fintech, edtech, e-commerce. First lesson: operating discipline separates engineers who ship from engineers who merely build.
Every system built in this period was for a founder who didn't have a senior technical person. The pattern was consistent: decisions that should have taken two hours took two weeks because there was no one with the authority and context to make them. The founders weren't incompetent. They were operating without the right person in the room. That observation is the entire basis for what Praxis does.
Full-Stack Engineer · Gurgaon
Engineer at a 30-person grocery startup doing exactly what Zepto and Blinkit do today. Watched at close range how wrong technical hires, deferred architecture decisions, and founder overextension compound into company-level failure. The product was sound. The operating infrastructure around it wasn't.
The company didn't fail because the market was wrong. It failed because the technical function was never built to support the pace of decisions the business needed. Architecture decisions were deferred until they couldn't be. The first senior hire came too late. This is the situation most 0-to-1 founders are in, and the one Deepak now exists to prevent.
Founder & CEO · Noida
Bootstrapped a technical practice from zero. 30+ clients across six countries. 20+ production systems shipped: from blockchain payment rails (KPMG Fintech Startup of the Year) to government edtech for the Maharashtra SSC Board, to NDIS compliance platforms in Australia and AI-driven enterprise CRM in the US.
Every engagement owner-operated. No institutional backing. Running a service business at this level teaches one thing above all: quality and volume cannot coexist. The decision to limit engagements, to go deep rather than wide, was the same decision that made each engagement worth having. It's also the operating principle that Praxis is built on.
Technical Architect · via Frecher Hinakins · Remote
Germany's largest independent car rental network was losing revenue to manual pricing. The problem was framed as a technology gap. It was a decision architecture gap, and the fix was a data processing layer, not a platform replacement.
The right diagnosis of the actual problem is the primary value a CTO delivers before a line of code is written. Starcar was about to spend seven figures on a new platform. The real solution cost a fraction of that and was live in weeks. Misdiagnosed technical problems are the most expensive kind.
Consultant CTO · Co-Founder · India · USA · Singapore
Brought in as Consultant CTO for India's first friendship app, now at 1.5M+ downloads across India and the USA. Operated across the full co-founder scope: architecture from zero, AI matching engine, engineering team, security and compliance, investor narrative. Concurrently co-founding Praxis, the fractional C-suite practice that makes this operating model available to 4–5 companies per year.
Built the team to 30 to hit launch targets, then systematically automated every manual workflow until 10 people were running what 30 had been running. CI/CD eliminated manual deployments. SOPs replaced ad-hoc decisions. Infrastructure automation eliminated manual monitoring. The saving wasn't just headcount. It was the organisational complexity that comes with headcount.
India
Primary market
Germany
Client delivery
United States
Client delivery
Australia
Client delivery
Singapore
Client delivery
UAE
Client delivery
AWS · GCP · Azure
Cloud platforms
SOC 2 · ISO 27001
Compliance delivered
GDPR · RBI
Regulatory frameworks
Alyke
1.5M+ users scaled
Frecher Hinakins
30+ engagements
SaaS · Mobile · CRM
Product categories
AI · ML Infra
Integration layer
Praxis
Operating now
Every engagement starts with a 45-minute diagnostic. No pitch. No deck. The founder describes where the company is stuck, technically, organisationally, or structurally. Deepak says what he sees, what he thinks is actually causing it, and whether he’s the right person to address it.
If there’s a fit, the engagement is scoped to a specific outcome with a specific timeline. Not an open retainer. A defined objective, a defined period, and a defined handover: systems documented, team operating independently, the founder removed from the loops that shouldn’t require them.
Fewer engagements than asked for. The founders who work with Praxis get everything. That’s only possible because attention isn’t distributed across ten companies simultaneously.
Structure
Retainer · Equity, scoped to outcome, not hours logged
Typical length
6–12 months, 3-month minimum, extend or exit clean at the milestone
Capacity
4–5 engagements a year. Selectivity is how quality is maintained
Stage
Seed · Series A–ready · Zero-to-one
Geography
India · Germany · USA · Remote globally
First step
45-min diagnostic: no obligation, no pitch, no deck
Bring the problem as it actually is, not the polished version. We’ll tell you what we see, what we’d do about it, and whether there’s a fit.