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
Choose an AI MVP agency by examining evidence, scope discipline, engineering controls, ownership, and communication. Do not rely on one universal price range, fixed scoring weights, or a claim that every capable team must ship within the same number of days.
Questions that reveal real capability
Product evidence
- Can the team show a live or recorded product with the client's permission?
- What failed during development, and how was it corrected?
- Which parts used AI, and which parts were ordinary software engineering?
Evaluation and safety
- How will output quality be measured before launch?
- What happens when the model is uncertain, unavailable, or changes behavior?
- Which actions require human approval?
- How are prompt injection, excessive permissions, and data leakage handled?
Scope and delivery
- What is included, excluded, and dependent on the client?
- What are the acceptance criteria for each critical workflow?
- How are changes estimated and approved?
- Which integrations are proven and which still need a POC?
Ownership and operations
- Who owns the repository, cloud account, domain, data, prompts, and deployment credentials?
- What documentation, tests, monitoring, and handover are included?
- Who responds after launch, under what terms?
How to compare proposals
Create your own weighted scorecard based on the project's risk. A regulated workflow may place more weight on security and auditability. A simple validation build may place more weight on speed and cost. The weights in any article are examples, not evidence-backed universal percentages.
Ask every vendor to quote the same scope and assumptions. Compare total responsibilities, not only the headline price. A cheaper proposal that excludes testing, deployment, model evaluation, or integration work may cost more later.
Techlign-specific claims
Techlign's current public website describes a Pakistan-based senior studio, reports 12 products shipped, says clients own the repository from day one, and describes work in two-week sprints. It does not currently publish the old fixed-price tiers or a universal 14-day guarantee. Any commercial claim in this article should match the live website and a dated proposal before publication.
Fact-check sources
- NIST AI Risk Management Framework
- NIST Secure Software Development Framework
- OWASP Top 10 for Agentic Applications 2026
- Techlign current homepage
- Techlign current work page
- Techlign current about page
Sources and product documentation can change. Recheck time-sensitive pages on the publication date.