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.

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AISD vs. LeewayHertz

LeewayHertz is a well-established AI development company with 200+ engineers and enterprise-scale delivery. AISD is an AI-native shop built for speed, transparency, and senior-only teams. Different buyers, different strengths. Here is an honest comparison.

Updated · 2026-05-02 · 5 min read

Side-by-side

The comparison

Factor	AISD	LeewayHertz
Team size	Senior-only. Every engineer ships code from day 1. No bench, no juniors backfilling	200+ employees. Mixed seniority. Account managers layer between you and the engineer
Speed	Working agent in 14 days, MVP in 6 weeks. Hard timelines in every proposal	Enterprise timelines. Typical engagements 3-6 months before production
Pricing transparency	Public pricing. Discovery sprints from $8K. MVPs from $50K. Staff aug from $75/hr	Hidden pricing. Contact sales for a quote. Typical projects $100K+
AI-native depth	Born AI-native. Every service is AI-first: agents, RAG, fine-tuning, eval harnesses	Full-service IT. AI is one of 20+ service lines alongside blockchain, IoT, metaverse
Engagement flexibility	Fixed-price projects, discovery sprints, fractional teams. No long-term contracts required	Enterprise contracts. Minimum engagement typically 3+ months
Process	The AISD Build Loop: scope tight, pattern-pick, build fast, secure by default, hand off with runbook	Traditional SDLC with discovery, design, build, test, deploy phases
Case studies	Numbers + architecture diagrams. 70% time reduction, $340K saved, 47% docs time cut	Logo-driven. Client names and industry verticals, lighter on quantified outcomes
Best for	Series A-C SaaS, mid-market, ops-heavy SMBs. Teams that need to ship fast with senior talent	Enterprise with large budgets, multi-year digital transformation programs

The honest take

When LeewayHertz is the better choice

LeewayHertz has more engineers, more case studies, and more enterprise logos than AISD. If you are running a multi-year digital transformation that spans blockchain, IoT, and AI simultaneously, their breadth is an advantage.

They also have a deeper bench for industries where regulatory compliance requires on-site teams or government clearances. AISD operates remote-first with distributed senior engineers.

When AISD is the better choice

If you need to ship a production AI agent in weeks rather than quarters, AISD's model is purpose-built for that. Every engineer is senior, every engagement has a hard timeline, and pricing is public before the first call.

AISD is also a better fit if your problem is specifically AI-native: agent orchestration, RAG pipelines, LLM eval, workflow automation. We don't dilute focus across 20 technology categories.

AISD vs. LeewayHertz

The comparison

When LeewayHertz is the better choice

When AISD is the better choice

See if AISD is the right fit.