AI cost, minus the hype.
AI app development cost: the model is cheap. Everything around it is not.
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Senior engineers
No juniors. No middlemen.
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Fixed price
Overruns are on us.
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Live in weeks
Weekly demos on staging.
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You own the code
100% of the IP, day one.
AI app development cost in 2026 ranges from about $10,000 to $300,000+. Vendor data puts basic AI apps at $10k–40k and complex AI products at $50k–300k+. The cost to integrate an LLM into an existing product is typically $15k–60k over 3–8 weeks. Regulated industries add roughly 20–40%. Data preparation, integration, testing and monitoring often cost more than the model. Token costs scale with usage and are budgeted separately.
AI cost by project type
| Project type | Typical scope | Indicative cost | Typical timeline |
|---|---|---|---|
| Basic AI app | Assistant over one data source, single LLM workflow | $10k–40k | 4–8 weeks |
| LLM integration into an existing product | Summaries, extraction, classification or search, with evaluation and guardrails | $15k–60k | 3–8 weeks |
| RAG / AI agent over private data | Ingestion, embeddings, retrieval, permissions, citations, tool use | $50k–150k | 2–5 months |
| Complex AI product | Multiple models, fine-tuning, real-time pipelines, high volume | $100k–300k+ | 4–9+ months |
| Regulated add-on | Audit trails, human review, data residency | +20–40% | +weeks, varies |
Vendor-published, approximate 2026 ranges (Empat, Azilen, Dreamz Tech). The RAG/agent band is our interpolation between published bands. Timelines are indicative.
The demo is free. Production is not.
An LLM demo takes an afternoon and works on the five examples you tried. Production has to work on the five thousand you did not, and cost a predictable amount per request.
Vendors agree: data preparation, integration, testing and monitoring often cost more than the model. A quote that is mostly prompt engineering, with no line for evaluation, is a demo quote.
What drives LLM integration cost
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Data readiness
Scanned PDFs can double the project
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Accuracy bar
Higher bar, bigger evaluation work
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Integration depth
Write-back to CRM or ERP
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Volume and latency
Caching, batching, smaller models
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Privacy
+20–40% in regulated industries
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Agentic actions
Permissions, sandboxing, more tests
One LLM integration, five regions
About 400 hours at senior rates. AI engineering is senior work; junior-heavy teams ship demos.
| Region | Senior hourly rate | 400-hour LLM integration |
|---|---|---|
| United States | $140–200+ | $56k–80k+ |
| Western Europe | $110–160 | $44k–64k |
| Central & Eastern Europe | $60–80 | $24k–32k |
| Latin America | $65–90 | $26k–36k |
| South / Southeast Asia | $42–55 | $16.8k–22k |
Vendor-published 2026 surveys (HireInSouth, SecondTalent), approximate. Specialist ML engineers can bill above these bands. See software developer rates.
Illustrative example: AI data entry
Illustrative example, not a quote. Extract fields from emailed supplier documents, route low-confidence results to a human, write approved data back. Approach: [replacing manual data entry with custom AI tools](/blog/replacing-manual-data-entry-with-custom-ai-tools).
| Work package | Hours | CEE senior $60–80/h | US senior $140–200/h |
|---|---|---|---|
| Discovery and accuracy target | 24 | $1.4k–1.9k | $3.4k–4.8k |
| Email ingestion, OCR / PDF parsing | 50 | $3k–4k | $7k–10k |
| Extraction prompts and output schema | 40 | $2.4k–3.2k | $5.6k–8k |
| Evaluation set and accuracy tests | 50 | $3k–4k | $7k–10k |
| Human review queue UI | 60 | $3.6k–4.8k | $8.4k–12k |
| Write-back integration | 50 | $3k–4k | $7k–10k |
| Logging, cost tracking, QA, deploy | 66 | $4k–5.3k | $9.2k–13.2k |
| Total | 340 | $20.4k–27.2k | $47.6k–68k |
Illustrative example. Prompts are about 12% of the hours; the rest is data, integration, evaluation and operations.
Token bills, kept small
Monthly cost = requests x tokens per request x price per token. Illustrative: 50M tokens at $1–10 per million is $50–500 a month.
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Route to smaller models
Easy requests go to cheap models. Hard ones go to frontier models.
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Cache results
Repeated prompts and results should never be paid for twice.
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Hard caps
A monthly cap per customer or feature. RAG and agent loops multiply tokens 5–20x.
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Log every call
Cost, latency and outcome from the first release.
AI we have shipped
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Medical AI That Drafts. Clinicians Decide.
AI software for a hospital: LLM-drafted clinical documents and imaging-report text, mandatory clinician review, full audit logs, GDPR health-data handling and an on-prem or private-cloud deployment option.
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See Our Sofa in Your Living Room
AI virtual staging for a furniture retailer: catalogue ingestion, room analysis, perspective-aware placement of real products, generative compositing, shopper UI and lead capture.
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Five AI Agents, One Fix Plan
Multi-agent LLM system: five specialist agents audit citability, authority, E-E-A-T, technical GEO, schema and platform presence, then a synthesis layer writes a weighted score and fix report.
Fixed AI scope. We eat the overruns.
After a free scoping call we send a fixed written quote for an agreed scope, including evaluation and monitoring. That price is what you pay; if our estimate was wrong, the extra hours are ours. Changes you request are quoted separately first. Token and hosting costs stay in your accounts, at cost.
See AI developmentQuestions buyers ask us
How much does it cost to integrate an LLM into an app?
Typically $15k–60k over 3–8 weeks for a production-quality feature in an existing product, per 2026 vendor data. A 400-hour integration costs about $24k–32k at CEE senior rates and $56k–80k at US rates. Token costs come on top.
How much does an AI app cost to build?
Basic AI apps run about $10k–40k. Complex AI products with custom pipelines, multiple models or high volume run $50k–300k+. Regulated industries add roughly 20–40%. The biggest driver is usually data readiness, not the model.
Is it cheaper to use an LLM API or host my own model?
For most companies a hosted API is cheaper until volume is very high or privacy rules require self-hosting, which adds GPU costs and operations work. Keep your code provider-agnostic so you can switch when prices change.
What does a RAG chatbot over company documents cost?
A basic version over one clean source can fit in $10k–40k. Production RAG with several sources, permissions, citations and evaluation typically lands in $50k–150k. Messy or scanned documents push it higher.
Why do AI projects go over budget?
Because the demo worked and the edge cases were never priced. Accuracy targets, evaluation, human review and integration are usually missing from early estimates. Write the accuracy bar into the scope, then price it.
Can you fix an AI-generated codebase?
Yes. We review it in a free code audit and tell you what to keep, refactor or rebuild. Read fixing AI-generated code. Security gaps and missing tests are the usual findings.
Keep reading
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AI development
Production AI, not demos. LLM integration, RAG, document processing and AI features built with evaluations, human review and GDPR-aware data handling.
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AI developers
Senior engineers who ship LLM features, RAG search and agents into real products, with evaluations, guardrails and cost control. Monthly augmentation or a fixed-price AI build.
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Healthcare
Clinical tools, patient portals and medical AI software with audit logs, consent handling and human-in-the-loop review designed in from the first sprint.
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Medical AI That Drafts. Clinicians Decide.
AI software for a hospital: LLM-drafted clinical documents and imaging-report text, mandatory clinician review, full audit logs, GDPR health-data handling and an on-prem or private-cloud deployment option.
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SaaS development cost
What it costs to build a SaaS product in 2026: launch ranges, the SaaS-specific features that add hours (billing, multi-tenancy, SSO), region rates and running costs.
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Free code audit
A free, no-obligation codebase audit by a senior engineer. You get a written report: what is healthy, what is risky, and whether to keep, refactor or rebuild.
Get a fixed price for your AI feature
Show us the workflow and the data. We will tell you what is worth automating and send a written quote.