Clarista's senior AI engineering team designs, builds, and deploys your generative AI app, ML system, or AI agent — on your cloud, governed by SOC 2 / HIPAA / ISO 27001 by default. Fixed-bid from $50K. No hourly drift. No 6-month "discovery." No Big-4 markup.
The "AI dev services" market is full of agencies that bill hourly, scope-creep aggressively, and ship apps that hit the production wall.
Typical AI dev agency builds the same infrastructure (auth, governance, observability, deployment) on every project. You pay for that re-work. Every time.
Discovery phase: 6 weeks. Design phase: 4 weeks. Build phase: 8-12 weeks. Compliance phase: indefinite. By month 6 the model and the market have moved.
Hit the security review and never pass. Hit the cost ceiling. Hit the scope-creep wall. The agency moves on — you're holding a $400K invoice and no live app.
We compress this to 4-8 weeks because the production plumbing is already done.
Pick the engagement that matches what you're building.
LLM-powered apps: copilots, RAG-based assistants, document processors, AI workflows. Built on Claude, GPT, Gemini, Llama — your choice.
Bespoke ML or AI application built end-to-end. Use when you need more than a wrapper around an LLM — domain models, agentic systems, deeply integrated tools.
Production agents with tool use, governance, eval loops, and observability. Built for real workflows — not chatbot demos.
Need something else — fine-tuning, vector DB design, voice AI, multimodal? Mention it on the scoping call. We'll either scope it or tell you who can.
We don't lock you into a runtime. Every AI development service deploys to your infrastructure, with your LLM, your data, your code.
No vendor lock-in. No proprietary runtime. The code we ship runs on your stack with or without us.
Four common ways enterprises get AI apps built — and why outsourcing to us wins on speed, cost, and ownership.
| Clarista | Generic AI Dev Agency | Big-4 / Globant | DIY (In-House Build) | |
|---|---|---|---|---|
| Time to production | 4-8 weeks | 3-6 months | 3-9 months | 6-18 months |
| Project cost | $50K-$250K fixed-bid | $200K-$600K (often T&M) | $300K-$1M+ | $400K-$2M loaded |
| Pricing model | Fixed-bid only | T&M, hourly drift | T&M with markup | Opportunity cost |
| Engineer seniority | Senior (5+ yrs avg) | Mixed (median junior) | Mostly junior, partner overhead | You hire and train |
| Infrastructure built each time | No — platform-backed | Yes — billed to you | Yes — heavily billed | Yes — your engineers |
| Compliance built in | SOC 2 + HIPAA + ISO default | Add-on, billed separately | Add-on, billed separately | You build it |
| Code ownership | 100% handoff to your Git | Varies — read SOW | Yours (but maintenance-heavy) | Yours |
| After-launch maintenance | Optional managed-service tier | Hourly retainer | Multi-year retainer | Your team |
No 6-week "discovery" billed at $30K. Straight to scoping, then build.
Bring your use case, your data, your constraints. We ask 10 questions and give you a fit/no-fit answer on the call.
Scope, deliverables, milestones, fixed price. We absorb scope-creep risk. You sign once and there are no surprise change orders.
Weekly demos. Direct Slack with the engineering team. Code commits to your Git as we go — not at the end.
App live on your infra. Code, architecture docs, runbook, controls evidence pack delivered. Optional 30-90 day managed support.
We're built for production AI apps with real users, real data, and real compliance requirements. Minimum budget: $50K per build.
If you need a quick prototype for an investor pitch, a free MVP, or commodity chatbots — we're not the right fit. Hire a freelancer on Upwork or use a no-code tool.
Right fit: CTOs and VPs of Engineering who have been quoted $400K+ by a Big-4 firm, have a real production AI use case, and want to ship in weeks instead of quarters.
Customer names redacted under NDA — references provided on the scoping call.
Fixed-bid $120K. Replaced a 9-month internal RFP process. SOC 2 controls inherited from Clarista. Processing 8,000 claims/day at launch.
Internal team had been working on this for 11 months. We shipped a working production app in 5 weeks. 40 analysts using it on day 1.
HIPAA-ready by default. Deployed on customer Azure tenant. The CMO compared the savings to "hiring an extra cardiologist for the year."
Anonymized to protect customer confidentiality. We can introduce you to a reference in your industry on the scoping call.
Most AI dev companies rebuild the same plumbing on every engagement. We don't. That's the entire reason this works.
Auth, multi-LLM orchestration, RAG indexing, governance, audit, RBAC, observability, eval framework, deployment pipeline — these are pre-built on Clarista. Generic AI dev agencies write them from scratch every project. That's why their builds cost 3x more and take 3x longer.
Every engineer assigned to your project is senior (5+ years production AI/ML). No junior tier we offload work to. The architect on day 1 is the engineer shipping code in week 4.
We absorb scope-creep risk. If we underestimate, we eat it — not you. This forces us to scope tight and execute fast. Most agencies hide behind hourly billing because their estimates are bad.
Apps deploy to your AWS, Azure, GCP, or on-prem. Code in your Git from day 1. No proprietary runtime. You can keep using Clarista as your AI app platform or run the code completely independently — your call.
20-minute scoping call. Bring the use case, the stack, the budget. Leave with a fixed-bid number and a 4-8 week delivery date.
Book scoping call →Three tiers: (1) Generative AI app builds — LLM copilots, RAG systems, agentic workflows. (2) Custom AI software — bespoke ML or AI applications built to your spec. (3) AI agent development — production agents with tool use, governance, observability. All fixed-bid from $50K, delivered in 4-8 weeks on your cloud.
Most AI dev companies bill $200K-$600K per project and take 3-6 months because they rebuild the same infrastructure on every project. We ship on the Clarista platform, so 70-80% is pre-built. Net effect: 3-5x faster, materially cheaper, governance baked in.
Yes. We deploy to your AWS, Azure, GCP, or on-prem. We integrate with your data warehouse (Snowflake, BigQuery, Databricks), SSO (Okta, Azure AD), and observability stack. BYO LLM — Claude, GPT, Gemini, Llama, or open-source models.
Fixed-bid pricing starts at $50,000 for a scoped generative AI app build. Most engagements range $50K-$250K. Compare to typical AI dev agencies at $200K-$600K, or in-house build at $400K+ when you factor 6-12 month engineering cycles.
Yes — for the 80% of AI apps that fit common patterns (copilots, RAG, agents, document processing, workflows). For custom model training or novel architectures, we scope longer (8-16 weeks). The scoping call tells us which bucket your project is in.
Everything: source code in your Git, the app deployed in your cloud, architecture documentation, ops runbook, and the controls evidence pack (SOC 2 / HIPAA / ISO 27001 mappings). No vendor lock-in.
Yes — optional. After handoff, you can engage us for managed services (on-call, monitoring, monthly improvement sprints) at a fixed monthly rate. Most clients use this for 3-6 months post-launch.
Projects under $50K, investor-pitch demos, or commodity chatbots aren't a fit. We're built for production-grade AI apps with real users, real data, real compliance requirements. If you need a cheap MVP, hire a freelancer on Upwork.
Yes — that's our AI Consulting service. Use it when you have budget but aren't sure which AI use case to prioritize. Many clients combine consulting (2-3 weeks) with a build (4-8 weeks) into a single engagement.
A market overview for buyers evaluating AI dev companies, custom AI software vendors, and generative AI development partners.
Generative AI development services build apps that use foundation models (Claude, GPT, Gemini, Llama) to generate text, code, images, or structured outputs. Most "generative AI development companies" focus on three patterns: copilots (assist a human inside a workflow), RAG-based assistants (answer questions over private data), and agentic workflows (multi-step tasks with tool use). Clarista builds all three — and the production plumbing (auth, governance, observability, evals) is pre-built so we ship in weeks instead of months.
"Custom AI software" usually means more than a wrapper around an LLM. It's a bespoke application — sometimes with fine-tuned models, sometimes with classical ML, sometimes mixed — built for your specific workflow. Custom AI software development engagements typically include architecture design, model selection (off-the-shelf vs fine-tuned), backend + frontend, data pipeline, deployment, and ongoing eval. Most custom AI software builds at agencies run 6-12 months. We compress to 5-10 weeks because we don't rebuild infrastructure each time.
"AI/ML development services" covers everything from classical ML (regression, classification, recommendation systems) to modern generative AI. The most common 2026 builds are in the generative AI category — LLM-powered applications — because the time-to-value is faster and the off-the-shelf model quality has crossed the production threshold for many use cases. We do both, but generative AI is where most production demand lives now.
When evaluating an AI application development company, the questions that matter: (1) Do they bill fixed or hourly? (Fixed forces discipline.) (2) Do they ship to your cloud or theirs? (Yours = no lock-in.) (3) What's the engineer seniority? (Junior staffed at senior rates is the most common scam.) (4) Is compliance built in or add-on? (Add-on means you pay twice.) (5) Do you own the code? (Read the SOW — many agencies retain "platform code.")
The conventional AI development services model — agency does 6 months of discovery + design + build + compliance — is the wrong unit cost for most 2026 production AI apps. Platform-backed AI development services (Clarista's model) ship in 4-8 weeks at one-quarter the cost because the infrastructure is amortized. Talk to our team →
20-minute scoping call. We listen, ask 10 questions, and tell you on the call whether we can ship what you need — and roughly what it costs.
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