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).

How is AISD different from a typical software development agency?

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.

How long does it take to build an AI MVP?

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.

What does an AI MVP cost?

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.

How do you ensure AI features are reliable in production?

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.

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

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.

What does it cost to build an AI agent?

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.

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

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.

Compare . AI development

AISD vs. Turing

Turing is a global talent cloud with 3M+ developers and AI-powered matching. AISD is a focused AI agency with senior-only teams that build and ship production systems. Different scale, different model.

Updated . 2026-05-02 . 5 min read

Side-by-side

The comparison

Factor	AISD	Turing
Model	AI-native agency. Coordinated senior squads build and ship your system end-to-end	Global talent cloud. Turing matches you with remote engineers from a pool of 3M+ developers worldwide
AI specialization	100% AI-focused. Every service, every engineer, every process is built around AI delivery	AI is one category among many. Turing staffs full-stack, mobile, DevOps, data, and AI roles
Team size & seniority	Small, senior-only squads. Every engineer ships code from day 1. No bench, no juniors	Large pool. Seniority varies. Turing uses AI-based vetting to filter candidates, but you still interview and select
Speed	Working agent in 14 days, MVP in 6 weeks. Hard timelines in every proposal	Engineer matching in 3-5 days. Production speed depends on your management and project complexity
Pricing	Public pricing. Discovery from $8K. MVPs from $50K. Staff aug from $75/hr	Transparent hourly rates. Typical senior AI engineer: $60-100/hr. Lower cost due to global talent pool
Delivery ownership	AISD owns the outcome. Architecture, implementation, eval, deployment, and handoff	You own the outcome. Turing provides the engineer. Project management is on your team
Best for	Teams that need a production AI system shipped fast without building an internal team to manage it	Teams with existing engineering leadership that need to add AI capacity at competitive hourly rates

The honest take

When Turing is the better choice

If you have a strong engineering org and need to add AI capacity at competitive rates, Turing's global pool gives you access to talent that might cost 2-3x in the US market. Their AI-powered vetting reduces hiring friction.

Turing also shines for long-term staffing needs where you want engineers embedded in your team for 6-12+ months. The per-hour economics get better over time.

When AISD is the better choice

If you need a production AI system and don't have the internal leadership to manage individual engineers, AISD delivers the whole thing. Architecture, build, evaluation, deployment, and handoff with a runbook.

AISD is also a better fit when speed matters more than cost per hour. A coordinated senior squad shipping in 6 weeks beats assembling and ramping individual engineers over months.

AISD vs. Turing

The comparison

When Turing is the better choice

When AISD is the better choice

See if AISD is the right fit.