Internal-claim note: Techlign-specific prices, timelines, project counts, rankings, client outcomes, and original research were not independently verifiable from the supplied file. Publish them only with internal records and a named methodology.
The practical answer
There is no single "real AI MVP cost." The total depends on product scope, data preparation, integrations, security, evaluation, support, and usage. Model tokens are often only a small part of the first-year cost.
Separate the cost into layers
- Product work: discovery, UX, frontend, backend, authentication, billing, and administration.
- AI work: prompt and tool design, retrieval, output schemas, evaluations, guardrails, and fallbacks.
- Data work: cleaning, permissions, indexing, migration, and ongoing updates.
- Integration work: CRM, EHR, payment, messaging, document, or internal systems.
- Production operations: hosting, monitoring, security, backups, incident handling, and support.
- Usage: model tokens, search or tool calls, vector storage, transcription, telephony, and other metered services.
How to estimate model spend
Use a representative sample of real requests. Record input tokens, output tokens, tool calls, cache behavior, retry rates, and the percentage of requests routed to each model. Multiply that measured profile by expected traffic and current official prices. Add a margin for retries and growth.
Do not copy a per-request figure from another product. A document workflow with long inputs can have a very different cost profile from a short classification task.
About the prices in this blog library
Techlign package prices and delivery windows are internal commercial statements. They are not independent market benchmarks. Before publication, confirm that each offer is still available and that the scope, exclusions, taxes, third-party fees, support period, and change process are stated clearly.
Better buying questions
- What exact workflow is included?
- Which integrations and data migrations are excluded?
- How will quality be measured before launch?
- Who pays for provider usage and support?
- What happens when a model or API changes?
- Is security review included?
- Who owns the code, accounts, prompts, and evaluation data?
A credible estimate connects cost to a written scope and measurable acceptance criteria. A headline number without those details is not comparable.
Fact-check sources
- HHS: HIPAA and cloud computing
- HHS: HIPAA Privacy Rule
- FDA: Clinical Decision Support Software guidance
- NIST AI Risk Management Framework
- NIST Secure Software Development Framework
- OWASP Top 10 for LLM Applications
- OWASP Top 10 for Agentic Applications 2026
Sources and product documentation can change. Recheck time-sensitive pages on the publication date.