State of Tech Due Diligence 2026: What Industry Data Tells Us About Buy-vs-Build, Architecture Risk and Vendor RFP Outcomes
Synthesis of public tech-DD data: M&A engagement cost ranges, architecture red-flag patterns, buy-vs-build decision outcomes, vendor RFP scoring effectiveness - drawn from ISO/IEC 25010, IEEE 29148, TOGAF, McKinsey, Gartner and named industry cohort.
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TL;DR
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- Public M&A tech-DD pricing places engagement cost in the 50,000-400,000 USD range for early-stage to mid-market software deals, scaling further for cross-border or regulated targets (BCG Tech Build playbook + IDC industry reporting 2024-2025).
- McKinsey Tech Trends 2024-2026 reports place tech-DD red-flag rate (any material technical risk surfaced) commonly above 60% for software-acquisition deals, with architecture and tech-debt findings dominating the top-three categories.
- IEEE 29148 spec adoption inside vendor RFP processes correlates with 20-40% reduction in scope-creep, per Forrester research surveys 2024-2025 on requirements engineering practice.
- Buy-vs-build outcome data from BCG and HBR Technology archives suggests buy decisions outperform build for non-core capabilities by a 2-to-1 margin on time-to-value, while build wins on differentiation-critical surfaces.
- Fractional CTO retainers cluster in the 8,000-25,000 USD per month band for Series A-B companies in 2026 public benchmarks, with sprint-mode engagements running 30,000-120,000 USD per defined deliverable (IDC and Gartner advisory data).
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Method
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This piece is a synthesis of public industry data, not a Pharos engagement count. Pharos contributes synthesis and advisory voice, anchored on 12+ years of cross-domain delivery across blockchain, FinTech, AI and SaaS under PhD-led research direction (Dr. Dmytro Nasyrov, Founder and CTO). Inputs include normative standards, analyst research and management-research archives. The standards backbone is ISO/IEC 25010 for software quality characteristics, IEEE 29148 for requirements engineering and TOGAF for enterprise-architecture governance.
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The analyst layer pulls from McKinsey Tech Trends, Gartner Hype Cycle methodology notes, BCG Digital, Technology and Data publications, Forrester Research and IDC reports. The management-research layer pulls from Harvard Business Review Technology archive and MIT Sloan Management Review.
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Numbers are reported as bands derived from named cohorts, not single-firm samples. Where a band spans multiple sources, the lower bound reflects boutique or early-stage engagement pricing and the upper bound reflects regulated or cross-border targets.
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M&A Tech-DD Cost Trends 2024-2026
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Tech-DD pricing varies across three axes: deal size, complexity tier and regulatory exposure of the target. Public benchmarks from BCG, IDC and tier-1 advisory data converge on the following bands.
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- Sub-25M USD deal value: tech-DD scope often runs 50,000-120,000 USD. Scope is narrow: code-quality scan, architecture interview, license and dependency review, basic security posture.
- 25M-150M USD deal value: 120,000-250,000 USD. Adds load and scalability assessment, cloud-spend audit, deeper IP and open-source provenance work, key-person dependency mapping.
- 150M USD and above: 250,000-400,000 USD baseline, scaling further for cross-border or regulated targets in FinTech, healthcare and defense. Adds penetration testing, compliance gap analysis (SOC 2, ISO 27001, HIPAA, PCI DSS), architecture-runway modeling.
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BCG Tech Build playbooks and IDC industry data align on a directional finding: buyers who skip a structured tech-DD on software-heavy deals see post-close cost overruns 30-50% higher than buyers who invest in a full tier-2 or tier-3 scope. The cost of the diligence itself is consistently the smaller risk. Across our 12+ years of cross-domain advisory work the same pattern holds: the diligence engagement is the cheapest line item in a deal where it surfaces a deal-stopping risk, and the most expensive omission in a deal where it would have.
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Architecture Review Findings: Common Red Flags by Industry Vertical
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Architecture reviews under ISO/IEC 25010 evaluate eight quality characteristics: functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability and portability. Public McKinsey and Gartner research clusters red-flag findings by vertical.
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- FinTech and payments: top findings are key-management drift, audit-log gaps under SOX and PCI DSS, ledger-reconciliation race conditions and over-reliance on a single cloud region. Forrester research from 2024-2025 places critical-finding rate above 70% on FinTech tech-DD engagements.
- Healthcare and HealthTech: PHI handling outside HIPAA-compliant boundaries, weak BAA chain-of-custody, legacy HL7 integrations bolted onto modern microservices without contract testing.
- SaaS and B2B platforms: multi-tenant data isolation gaps, noisy-neighbor performance issues, feature-flag debt and missing observability for SLA-bound endpoints.
- E-commerce and marketplaces: inventory-consistency bugs under load, payment-gateway lock-in, search-relevance debt, fraud-rule maintainability.
- Industrial and IoT: firmware update channel integrity, OT and IT segmentation, time-sync assumptions baked into business logic, supply-chain provenance for embedded components.
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Across verticals, McKinsey Tech Trends archives consistently surface three structural red flags: tech-debt concentration in a small number of services, single-point-of-failure dependence on one or two senior engineers and observability that does not extend to the customer-impacting paths. In our advisory work across blockchain, FinTech, AI and SaaS targets these three flags travel together more often than not; finding any one of them on a tech-DD raises the prior probability of finding the other two.
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Buy-vs-Build Decision Patterns: Public Data on Outcomes by Org Maturity
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The buy-vs-build question is not symmetric across maturity stages. HBR Technology and MIT Sloan Management Review archives, combined with BCG digital-transformation case studies, point to a consistent pattern.
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- Pre-product-market-fit: build only the differentiator, buy everything else. Public outcome data shows founders who custom-build commodity infrastructure (auth, billing, analytics, search) before product-market fit underperform on runway by 4-9 months on average.
- Series A-B scale-up: the build threshold is the surface that drives unit economics or moat. Buy decisions on edge platforms, monitoring, data warehousing and identity continue to outperform build on time-to-value by roughly 2-to-1.
- Series C and later, plus enterprise: build returns at the integration and orchestration layer. Public BCG and McKinsey data shows large enterprises that adopted reference-architecture build patterns (event-driven backbones, internal developer platforms) outperformed pure-buy peers on 5-year TCO.
- Regulated industries: buy decisions face an additional compliance-portability test. Forrester research notes buyers who underestimate vendor lock-in on data residency and audit-trail export incur 15-30% higher 3-year cost than the build alternative they originally rejected.
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The cleanest decision frame in the public literature is the BCG one: build only when the capability is differentiation-critical AND the team has the architecture maturity to maintain it for at least 3 years. Across our 12+ years of cross-domain work the failure mode we see most often is teams passing the differentiation test but failing the architecture-maturity test; the build then ships on schedule and ages badly.
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One nuance the public literature emphasizes is that the buy-vs-build axis is rarely binary in practice. Most mature engineering organizations operate on a buy-extend-build spectrum: buy a base capability, extend it through configuration or plug-in surface area and build only the proprietary differentiator on top. McKinsey Tech Trends 2024-2026 highlights this composite pattern as the dominant operating mode for digital natives at Series C and beyond, with internal developer platforms acting as the connective tissue between bought components.
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Vendor RFP Scoring: What Public Frameworks Get Right and Wrong
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Vendor RFPs in 2026 still rely heavily on weighted scorecards. Public framework guidance from TOGAF ADM phases B through D and from IEEE 29148 requirements specification offers two strong patterns and several recurring failure modes.
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What public frameworks get right. TOGAF ADM forces buyers to define target architecture before scoring vendors, which prevents the most common RFP failure: scoring on capabilities the buyer does not actually need. IEEE 29148 spec patterns force functional, non-functional and constraint requirements to be separately enumerated, which materially reduces ambiguous scope. Forrester research 2024-2025 places the scope-creep reduction at 20-40% when IEEE 29148 patterns are followed end-to-end.
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What public frameworks get wrong. Weighted scorecards routinely under-weight three factors that dominate post-contract regret in the public literature: vendor change-management cost, integration cost into existing systems and exit cost. McKinsey and BCG case studies on failed transformations consistently identify exit-cost neglect as the top-three avoidable failure mode. Public RFP templates also tend to score architecture maturity by document presence rather than evidence quality, which is the single largest signal-to-noise problem in vendor selection.
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A second pattern worth naming: public RFP frameworks rarely require the buyer to commit, in writing, to the post-contract operating model. Who owns the integration runtime, who owns observability and who owns the off-ramp. TOGAF ADM phase F and G give the buyer the language to specify governance and change-management contracts, but most public RFP templates stop at phase E. The gap between target architecture (phase D) and implementation governance (phases F-G) is where the most expensive vendor-relationship surprises live. In our experience advising clients on vendor selection this is also the gap that causes the most expensive procurement regrets, ahead of price misjudgement or feature-fit miss.
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The Fractional CTO Reality: When Retainers Win, When Sprints Win
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Fractional CTO arrangements split into two structural shapes in the public benchmark data. Retainers run continuously and bias toward governance, hiring and roadmap. Sprint engagements bias toward a defined deliverable: an architecture decision record, a platform migration plan, a tech-DD report.
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- Retainer band: 8,000-25,000 USD per month for Series A-B companies in 2026 public benchmarks. The retainer wins when the company has structural decisions monthly and needs a senior counterweight to the founder or VPE.
- Sprint band: 30,000-120,000 USD per defined deliverable. The sprint wins when the company has a single high-stakes decision (acquisition, replatforming, regulatory entry) and clear scope.
- Anti-pattern: retainer used as a permanent extension of capacity. IDC and Gartner advisory data flags this as a failure mode where the fractional engagement displaces hiring rather than enabling it.
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The cleanest test in the public literature: a retainer should reduce the number of decisions reaching the CEO that should never have reached the CEO. If the count is not falling at month three, the engagement shape is wrong.
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Tech-Debt Detection Rate: Public ISO/IEC 25010 Quality Model Outcomes
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Tech-debt detection follows a predictable distribution under ISO/IEC 25010 assessments. Public outcome data from analyst case studies and academic empirical-software-engineering literature clusters as follows.
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- Maintainability findings: surfaced in roughly 85-95% of assessments. Modularity, reusability and testability deficits dominate. This is the most reliable category for cost-overrun prediction.
- Reliability findings: 60-80% of assessments. Recoverability and fault tolerance gaps cluster in companies that scaled past their original architecture without a formal review.
- Security findings: 70-90% of assessments. Confidentiality and authenticity deficits are the most common, followed by accountability gaps.
- Performance efficiency findings: 50-70% of assessments. Capacity and resource-utilization issues dominate over time-behavior in modern cloud-native systems.
- Portability findings: 40-60% of assessments. Cloud-vendor adaptability is the dominant subcategory in 2024-2026 due to the cloud-cost rationalization wave.
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The pattern is consistent across McKinsey and Forrester reporting: tech-debt is found, the question is whether the buyer has a remediation plan and a budget that matches the finding severity.
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One pattern worth surfacing separately: maintainability findings disproportionately predict the cost of every other remediation. Public empirical-software-engineering studies indexed in ISO/IEC 25010 assessment literature show that systems with low maintainability scores cost 2-3x more to fix any given reliability or security finding compared with systems scored healthy on the same characteristic. Maintainability is not a soft finding, it is a multiplier on the bill for every other category. Across our 12+ years of cross-domain delivery this multiplier is the single most reliable input to a remediation budget; we model maintainability findings as a coefficient on every other line item, not as a standalone cost.
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Cost-vs-Confidence Decision Matrix by Engagement Type
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The four common technical-advisory engagement shapes have different cost-vs-confidence profiles. Public benchmark data supports the following matrix.
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- Code or architecture audit: 15,000-80,000 USD typical scope. High confidence on existing-system risk, low confidence on forward-looking strategy. Best for pre-funding or pre-acquisition snapshot.
- RFC or architecture decision record: 20,000-60,000 USD typical scope. High confidence on a single forward decision, low confidence on broader system context. Best when a specific bet is on the table.
- M&A tech-DD: 50,000-400,000 USD typical scope per the bands above. High confidence on deal-stopping risk, moderate confidence on post-close integration cost. Best as a go or no-go gate.
- Fractional CTO retainer: 8,000-25,000 USD per month. Moderate confidence on any single decision, high confidence on cumulative governance quality over 6-12 months. Best when the company is decision-rich.
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The matrix is not a ranking. The right choice depends on whether the buyer needs a snapshot, a single decision, a deal gate or sustained governance. Public BCG and HBR case studies are clear that mismatching engagement shape to need is the dominant cause of dissatisfaction with technical-advisory work, ahead of price.
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Methodology Caveats and Limitations
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Three caveats apply to every band in this piece.
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First, public benchmark data skews toward funded software companies in North America and Western Europe. Emerging-market and bootstrapped-company data is under-represented in the named cohort, which means lower-bound pricing in this piece is conservative for those segments.
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Second, ISO/IEC 25010 detection rates depend on assessment depth. A two-week scoping engagement and a six-week deep dive surface different distributions. The bands above assume a tier-2 to tier-3 scope, not a one-week scoping pass.
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Third, the buy-vs-build literature is heavily case-study driven. HBR, MIT Sloan and BCG archives document outcomes but do not control for selection bias on which companies publish their decisions. Outcome ratios should be read as directional, not as causal proof.
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None of the numbers above replace a scoped engagement with a named target. They are directional bands meant to calibrate expectations before scoping. If your situation falls outside the bands, that is a signal to ask why, not a signal to anchor on the median.
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Pharos Production has been in business since 2013, with over 13 years of experience in custom software development. During this time, we have delivered over 70 applications for 200+ clients across 18 industries, including FinTech, healthcare, crypto and e-commerce. We are rated 5/5 on Clutch based on 73 verified reviews (2026).
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Pharos Production provides six core service categories: Software Development (mobile apps, web platforms, database design, UI/UX), Blockchain Development (smart contracts, DeFi, tokenization on Ethereum, Solana, TON and other chains), Software Security (code audits, penetration testing, smart contract audits), Software Consulting (architecture design, MVP validation, startup consulting) and Software Testing and QA (manual, automation, performance and regression testing).
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Pharos Production is headquartered in Las Vegas, Nevada, USA (5348 Vegas Dr, Las Vegas, NV 89108), with an engineering office in Kyiv, Ukraine (44-B Eugene Konovalets Str. Suite 201, Kyiv 01133). We work with clients worldwide and provide remote collaboration across all time zones. Visit our contact page for directions and scheduling options.
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Pharos Production has a team of 90+ engineers, including software developers, blockchain specialists, QA engineers, DevOps experts, UI/UX designers, project managers and solution architects. Our founder, Dr. Dmytro Nasyrov, holds a PhD in Artificial Intelligence and leads the technical direction of all projects.
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We serve a wide range of clients, from startups and product companies to mid-sized enterprises and large institutions. Our clients include crypto exchanges, FinTech providers (like Pleenk), healthcare organizations, sportsbook operators (like Pro Gambling), e-commerce platforms and SaaS companies. Pharos Production has worked with 200+ clients across 18 industries since 2013, adapting engagement models to match each client’s stage, whether it is MVP validation for a startup or enterprise-scale development for an established business.
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A custom software development company is a firm that designs, builds and maintains software tailored to a specific business’s needs, as opposed to off-the-shelf products. Custom software addresses unique workflows, integrations and scalability requirements that generic tools cannot. According to Grand View Research (2024), the global custom software development market is valued at over $35 billion and is projected to grow at a 22.3% CAGR through 2030. Pharos Production is a custom software development company founded in 2013, with a team of 90+ engineers delivering solutions across blockchain, FinTech, healthcare and 15 other industries.
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Custom software development costs vary based on project scope and complexity. At Pharos Production, typical project ranges are: MVP development ($10,000-$25,000), suitable for startups validating a product idea; full-fledged production ($25,000-$50,000), for established businesses scaling a proven concept; and full-cycle development ($50,000-$80,000+), for complex enterprise-grade systems. These ranges include architecture design, development, QA testing and deployment. Final pricing depends on technology stack, number of integrations and engagement model (staff augmentation, dedicated team or project outsourcing).
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Development timelines depend on scope and complexity. At Pharos Production, a typical MVP takes 2-4 months, a production-ready application takes 4-8 months and a complex enterprise system can take 8-12+ months. We use an agile methodology with 2-week sprints, delivering working increments after each sprint. Every sprint includes a retrospective, progress report and planning session for the next iteration. This approach ensures transparency and allows businesses to launch faster by prioritizing high-impact features first. Get a timeline estimate for your project.
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Pharos Production serves 18 industries: Crypto, Web3 and Blockchain (Kimlic, GridTradeX, NextCheck), Sports and Sportsbooks, Casino and Gambling (Gambit Stream, Lucky Bets), FinTech, Healthcare, E-Commerce, Insurance, Energy and Utilities, Education, Telecom, Media and Entertainment, Logistics and Transportation (Taxi Aggregator), Marketing, Banking, Construction and Real Estate, Agriculture and Travel. Our deepest expertise is in FinTech, blockchain and healthcare, where we have delivered compliance-ready platforms (HIPAA, PCI DSS, GDPR) and high-load systems handling thousands of concurrent users. For the latest industry insights, read our guides on FinTech trends in 2026 and the Web3 technology stack.
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Hiring a software development company offers faster time-to-market, lower upfront costs and access to specialized expertise without long-term employment commitments. According to Deloitte’s 2024 Global Outsourcing Survey, 57% of companies outsource software development to access skills they cannot hire internally.
Factor In-house team Software development company Time to assemble 3-6 months (recruiting + onboarding) 1-2 weeks Upfront cost High (salaries, benefits, equipment) Lower (project-based pricing) Specialized expertise Limited to who you can hire locally Access to 90+ engineers across blockchain, AI, FinTech Scalability Slow (each new hire takes months) Fast (scale up or down per sprint) Long-term commitment Full-time employment contracts Flexible engagement models Risk High if key engineers leave Company ensures continuity and knowledge transfer For businesses that need blockchain, AI or high-load architecture expertise, outsourcing to a specialized firm like Pharos Production reduces risk and accelerates delivery.
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Pharos Production focuses on mid-to-large custom software projects with budgets starting at $10,000. We do not take on template-based websites, WordPress theme customization, or short-term contracts under one month. We also do not provide non-technical staffing (marketing, sales or design-only roles). Our strongest fit is blockchain, FinTech and healthcare projects where security, compliance and high-load architecture are critical. For smaller projects or MVPs under $10,000, we recommend exploring freelance platforms or no-code tools as a more cost-effective starting point.
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We use agile with 2-week sprints because it reduces the risk of building features that miss the mark. Each sprint ends with a working demo, a retrospective and a plan for the next iteration.
This means clients see progress every 14 days and can adjust priorities based on real results, not assumptions. According to the Standish Group CHAOS Report (2024), agile projects are 3x more likely to succeed than waterfall projects. We chose this approach after years of experience showing that rigid, fixed-scope contracts lead to scope creep, missed deadlines and products that do not match market needs by launch day.
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Custom development is not the right choice in every situation. You should not hire a custom software company if: your problem is fully solved by an existing SaaS product (e.g. Shopify for e-commerce, Salesforce for CRM); your budget is under $10,000 and timeline is under 4 weeks; you need a simple landing page or marketing website (WordPress or Webflow is faster and cheaper); or you are still validating the idea and have not spoken to potential users yet.
In these cases, off-the-shelf tools or no-code platforms offer better ROI. Custom development makes sense when you need unique workflows, regulatory compliance, high-load architecture or competitive differentiation that packaged software cannot provide.
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Here are three anonymized examples from our recent delivery history:
FinTech startup - payment platform (MVP)
Scope: mobile app + backend API with bank-grade encryption. Team: 4 engineers, 1 QA. Timeline: 10 weeks. Budget: $38,000. Result: launched on schedule, processed $2M+ in transactions within the first quarter.Healthcare provider - patient portal (Full product)
Scope: HIPAA-aligned web platform with EHR integration, appointment scheduling and telemedicine. Team: 6 engineers, 1 DevOps, 2 QA. Timeline: 6 months. Budget: $120,000. Result: 15,000+ active patients, zero compliance violations in two annual audits.Crypto exchange - trading engine (Complex)
Scope: high-load matching engine handling 50,000+ orders per second, multi-chain wallet infrastructure on Ethereum and Solana. Team: 8 engineers, 2 QA, 1 security auditor. Timeline: 11 months. Budget: $340,000. Result: 99.97% uptime, passed three independent security audits.See more projects: NoMoreBets, Pulse, Sagas, Gambit Stream and Pleenk. For the full portfolio, visit our case studies. Learn more about the technology behind these projects in our guide to stablecoins and crypto infrastructure.
Role: Founder and CTO, Pharos Production
Focus: Architecture, Web3 products, smart contract security, high-load systems
Experience: 23 years in production delivery
