Question 1

What does AISD do?

Accepted Answer

AISD is an AI-native software development company that builds production AI for mid-market and enterprise teams. Three core services: AI Modernization (embedding AI into existing products — copilots, intelligent search, predictive analytics), AI Agents (autonomous workflows for support, document processing, sales outreach), and AI Workflow Automation (n8n, Zapier, Make, Clay).

Question 2

How is AISD different from a typical software development agency?

Accepted Answer

Three differences. First, every AISD engineer is senior — minimum 5 years building production software, with shipped AI features. Second, we publish hourly engagement bands and project ranges so you know roughly what an engagement costs before the first call. Third, we take fewer concurrent projects so a partner stays close to delivery.

Question 3

How long does it take to build an AI MVP?

Accepted Answer

Most AI MVPs at AISD ship a usable version in 4–8 weeks. Week 1 is a discovery sprint. Weeks 2–6 are the build, with weekly demos and a working version by week 4. Weeks 7–8 harden, document, and hand off.

Question 4

What does an AI MVP cost?

Accepted Answer

AISD AI MVPs typically range $45,000–$120,000 depending on scope. Drivers: number of model integrations, complexity of retrieval/data layer, custom UI surface area, and compliance requirements. We publish indicative bands on the pricing page so buyers can budget before the first call.

Question 5

How do you ensure AI features are reliable in production?

Accepted Answer

Five layers: an offline eval harness with golden test sets run on every PR; confidence thresholds and structured-output validation that gate downstream side effects; runtime observability — every model call logged with inputs, outputs, latency, cost; circuit breakers and deterministic fallbacks for every model dependency; and a weekly review ritual where prompt regressions get caught before they become incidents.

Question 6

How long does it take to build a production AI agent?

Accepted Answer

Working prototype: 2 weeks. Production-grade agent (with eval harness, guardrails, observability, and a runbook): 6–10 weeks. The prototype-to-production gap is where most projects fail — the prototype handles the happy path; production has to handle the long tail.

Question 7

What does it cost to build an AI agent?

Accepted Answer

A production AI agent at AISD typically costs $40,000–$150,000 depending on complexity. Drivers: number of integrated systems, evaluation rigor required, compliance overhead, and ongoing operational scope. Prototypes alone are cheaper ($10k–$25k) but rarely worth it without a path to production.

Question 8

How does pricing work — fixed-price, T&M, or retainer?

Accepted Answer

All three. Fixed-price for AI MVPs and agent builds where scope is well-defined after a discovery sprint. Time-and-materials for staff augmentation, billed monthly with a not-to-exceed ceiling. Retainer for ongoing optimization, eval-harness operations, and managed AI services — flat monthly fee for a defined scope of capacity.

Real customers. Real numbers.

Clinical document agent reduced doctor documentation time by 47%

Fintech MVP shipped at 60% lower cost, 2x faster

15-year-old C# WPF to modern cloud platform in 9 months

70% faster order processing, $340K saved annually

Regression testing: 3 weeks to 4 hours

Claims triage agent: 4 hours to 12 minutes per claim

SaaS onboarding copilot: 60% faster time-to-value

Resume parser pipeline: 85% faster screening

Listing agent: 3x faster property descriptions

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