eight vendor pages read september 2026
Generative AI development services and what LLM development actually costs
We opened eight generative AI vendor pages and wrote down three things: the price, the headquarters, and who owns the model at the end. Five published no price at all. The three that did disagree with each other by about sixteen times. None of the eight said a word about model ownership.
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the short answer
Generative AI development services are sold almost entirely without prices. Of eight vendor pages read in September 2026, none published an hourly rate and only three published a project band. Those three bands run from $5,000 to $500,000 for work all of them call generative AI development, a spread of roughly sixteen times. Converted at the category median of about $74.50 an hour, the same phrase is being quoted as anything from 0.4 to 42 engineer months. Separately, not one of the eight stated who owns the fine tuned weights, prompts or evaluation sets your money produces, which in a generative AI project is the part a standard software contract tends to miss. Compare vendors in engineer months, and name every model artifact in the contract before you sign.
The audit
What eight generative AI development company pages actually disclose
These are the vendors ranking for this term in the US. We read the main generative AI service page of each one and recorded only what is printed on it. Two more, Kellton and Markovate, blocked automated reading and are excluded rather than guessed at.
| Vendor | Headquarters disclosed | Hourly rate | Project price published | Model ownership stated |
|---|---|---|---|---|
| Appinventiv | Noida, India | None | $100,000 to $500,000 per project | No |
| Azilen | Ahmedabad, India | None | $20,000 to $80,000 proof of concept; $70,000 to $300,000 and up in production | No |
| Itransition | Not stated (10+ development centers) | None | $5,000 entry automation; $30,000 to $40,000 custom | No |
| Symphony Solutions | Amsterdam, Netherlands | None | None | No |
| Rishabh Software | Not stated (US, UK and Australia phone lines) | None | None | No |
| TechAhead | Not stated (markets dedicated offshore teams and GCC) | None | None | No |
| SoluLab | Not stated | None | None | No |
| LeewayHertz | Not stated | None | None | No |
Three numbers come out of that table. Zero of eight publish an hourly rate. Three of eight publish a project band. Zero of eight say who owns the model artifacts. The third number is the one nobody talks about, and it is the one that costs the most to get wrong.
The location column is worth reading twice. Only three vendors state a headquarters at all, and two of those three are in India. TechAhead is the most candid of the group: it openly markets dedicated offshore teams and global capability centers, while never saying which country. That is not dishonest, but it does mean a buyer who assumes American delivery from an American looking website is assuming it without evidence. We ran the same check across the broader category and published the results on AI development companies in USA, where six of eight vendors advertising a US address disclosed engineering somewhere else.
The sixteen times spread
Every published quote, converted into engineer months
Dollar figures from different vendors are not comparable, because each one bundles a different amount of work. Engineer months are comparable. Below, each published band is divided by $74.50 an hour, the midpoint of the $50 to $99 band that 13 of 20 vendors in the directory listing occupy, and then by 160 hours to get months.
| Published price | Vendor and what they call it | Implied hours | Engineer months |
|---|---|---|---|
| $5,000 | Itransition, entry level workflow automation on low code AI platforms | 67 | 0.4 |
| $20,000 | Azilen, focused proof of concept (low end) | 268 | 1.7 |
| $30,000 | Itransition, custom solution for one or two workflows (low end) | 403 | 2.5 |
| $40,000 | Itransition, custom solution for one or two workflows (high end) | 537 | 3.4 |
| $80,000 | Azilen, focused proof of concept (high end) | 1,074 | 6.7 |
| $100,000 | Appinventiv, typical project (low end) | 1,342 | 8.4 |
| $300,000 | Azilen, production generative AI feature (stated high end) | 4,027 | 25.2 |
| $500,000 | Appinventiv, typical project (high end) | 6,711 | 41.9 |
Read the two middle rows together. Itransition prices a custom generative AI solution covering one or two workflows at $30,000 to $40,000. Azilen prices a proof of concept, which is by definition less finished, at $20,000 to $80,000. At the top of its range Azilen's throwaway prototype costs twice Itransition's production system. Both descriptions are honest. They are simply pricing different amounts of engineering behind the same words.
This is why a shortlist built on quoted price alone tells you nothing. A $100,000 proposal is not expensive or cheap until you know whether it contains 8 engineer months or 3. Ask every vendor for the blended rate they used and the hours they assumed, then rebuild the table above with their own numbers. Any vendor unwilling to give you both has priced the project on what they think you will pay rather than on what it takes to build.
One caution on the arithmetic: $74.50 is a category midpoint, not any specific vendor's rate. Appinventiv and Azilen both engineer primarily in India, where directory rates run $25 to $49, so their true implied hours are higher than the table shows. That makes the spread wider, not narrower.
What the hourly rates look like
A US address does not predict a higher rate
Because no vendor publishes rates directly, the only hourly figures in this category come from directory listings. We took the twenty vendor ranking eSpark Info publishes for generative AI development and grouped it by band. The result contradicts the assumption most buyers start with.
| Listed hourly band | Vendors | Share | Where those vendors are listed |
|---|---|---|---|
| Under $25 | 1 | 5% | Delaware and India (one firm, both listed) |
| $25 to $49 | 5 | 25% | Virginia (two), New Jersey, Ukraine, India |
| $50 to $99 | 13 | 65% | Poland (two), Canada (two), Czechia, Romania, Costa Rica, Argentina, Pakistan, England, California, Maine, Pennsylvania |
| $100 to $149 | 1 | 5% | Austin, Texas |
Eight of the twenty list a US location, and they are scattered across every band. Two Virginia firms sit at $25 to $49, below two Polish firms at $50 to $99. The single most expensive band belongs to a company in Austin, and the cheapest to a firm listing Delaware alongside India. Whatever a US address signals in this market, it is not price.
Minimum project size splits differently and is more useful for self selection. One vendor accepts $1,000, three accept $5,000, eight set $10,000, five set $25,000 and two set $50,000. The two highest minimums belong to firms in Romania and Bengaluru, not the United States. If your budget is under about $10,000 you are outside the agency market entirely and better served hiring generative AI developers directly.
The clause everyone forgets
Who owns the model after a generative AI development company builds it?
Whatever your contract says, and none of the eight vendor pages we read said anything. This matters more in generative AI than in ordinary software, because most of what your money buys is not source code.
Fine tuned weights and adapters
A LoRA adapter trained on your data is a derivative of a base model you do not own. Say explicitly that the adapter and the training run belong to you, and that the vendor keeps no copy.
The system prompt library
Weeks of iteration end up encoded in prompts. They are text files, not code, and a work product clause written for software may not clearly cover them.
The evaluation set
The graded examples that prove the system works are the most reusable asset in the project. Without them you cannot verify a replacement vendor, which is exactly why you want them.
The retrieval index and chunking config
Embeddings, chunk sizes and the retrieval strategy took real experimentation. Ask for the configuration and the pipeline that regenerates it, not just the resulting database.
Synthetic training data
Data generated during the build is often produced under a model provider terms of use that restricts training competing models. Confirm which provider and which terms.
Your data as training input
State whether your production data may be sent to a third party model provider, and whether that provider may train on it. This is a data protection question before it is an IP question.
The practical test is simple. Send the vendor one sentence: on final payment, all fine tuned weights, adapters, prompts, evaluation sets, retrieval configurations and generated datasets become our property, and you retain no copies. A vendor who agrees in writing within a day has thought about this. A vendor who needs three weeks and a legal review has not, and that delay is itself useful information about how the engagement will run.
None of this makes the vendors in the audit untrustworthy. Marketing pages are not contracts, and most of these firms will sign a reasonable assignment clause if asked. The point is that you have to ask, because the category has not standardized on it the way ordinary software development has.
Scope
What is included in generative AI development services
Vendor pages describe scope in language broad enough to cover anything. Underneath the wording, a generative AI build is five workstreams, and the budget is not distributed the way most buyers expect.
Use case selection and feasibility
Deciding what to build and whether your data can support it. Sold separately as generative AI consulting, and the place where a discovery phase either earns its fee or repeats what you already knew.
Data access and retrieval engineering
Getting to the documents, records and systems the model needs, then chunking, embedding and retrieving them well. Usually the largest single line and the one most often underestimated.
The application layer
The interface, orchestration, tool calls, permissions and audit trail around the model. Conventional software engineering, and the part where ordinary development rates should apply.
Evaluation
Building a graded test set and measuring output quality against it. Skipping this is why pilots feel impressive and production systems disappoint. Insist it is a named deliverable.
Production operations
Token cost control, latency, caching, fallback models, monitoring and drift. A generative feature has a running cost per request, unlike most software you have bought before.
The model call itself
The smallest piece by a wide margin. Any vendor whose proposal is mostly about model selection has not understood where the work is.
The label attached to all this varies by vendor and means very little. LLM development services usually signals text work: retrieval augmented generation, assistants, summarization, fine tuning. Generative AI development is the wider umbrella that also covers image, audio, video and code generation. A generative AI consulting company sells the first workstream on its own. In practice the same engineers deliver all three, so buy on the artifact you need rather than the category name. If the artifact is specifically a retrieval system, the scoping detail sits on our RAG development services page, and if it is an autonomous workflow rather than a single feature, on AI agent development company.
Making quotes comparable
Six requirements that force honest proposals
Send the identical brief to three vendors and require these six things in every response. The differences between the answers will tell you more than any ranking list.
The blended hourly rate and the assumed hours, separately
Without both you cannot convert the quote into engineer months, and without that you cannot compare two proposals at all.
Discovery priced apart from build
A bundled figure hides how much of your budget is being spent deciding what to do versus doing it. Consulting heavy vendors bundle by default.
The delivery country for each named engineer
Only three of eight vendors state a headquarters. Get it per person and put it in the statement of work, not the sales call.
The accuracy threshold and how it will be measured
Ask for a target on an agreed evaluation set. A vendor who will not commit to a measurable quality bar is selling a demo.
The running cost per thousand requests at expected volume
Generative features cost money every time they run. A build quote without an operating estimate is half a price.
The ownership sentence from section 04, agreed in writing
Weights, adapters, prompts, evaluation sets, retrieval configuration and generated data, assigned to you on payment, with no copies retained.
By what you need built
Go straight to the work rather than the vendor category
Most people searching for generative AI development already know roughly what they want built. If that is you, these are the direct routes.
LLM development company
Custom LLM work specifically: fine tuning, private deployment and language pipelines.
Hire generative AI developers
Individual senior engineers instead of an agency team, when the spec is already clear.
AI development company
The broader category page covering scope, engagement models and how builds are structured.
AI consulting firms compared
When the hard part is deciding what to build rather than building it.
AI proof of concept
Prove the use case works before committing a six figure build budget.
Enterprise AI development
Larger programs with procurement, security review and multiple stakeholders.
The honest version
Where BotGigs fits, and where it does not
We are not a generative AI development agency. BotGigs is a hiring marketplace: you describe the generative AI work in a brief, and we match it to vetted AI and automation specialists, with rates and location visible before you commit and hire fees published on our pricing page rather than folded into a project figure.
That is the right answer when you know the workflow you want built, the systems it touches and how you will judge success, and you would rather pay for engineering than for an account manager. It is the wrong answer when you need one vendor to own a multi year program across several business units, carry the change management and sign up to a business outcome. For that, hire one of the firms above, and hold them to the six requirements in section 06.
Questions
Questions buyers ask about generative AI development services
How much does generative AI cost to build?
The three vendors we found who publish anything quote between $5,000 and $500,000 for work they all describe as generative AI development. Itransition lists $30,000 to $40,000 for a custom solution covering one or two workflows, Azilen lists $70,000 to $300,000 and up for a production feature, and Appinventiv lists $100,000 to $500,000 per project. At the category median rate of about $74.50 an hour that is 2.5 to 42 engineer months of work, which is the only way to compare them.
Do generative AI development companies publish their prices?
Not one of the eight service pages we read in September 2026 published an hourly rate. Three published project bands instead, and those bands disagree by roughly 16 times for nominally the same deliverable. The only hourly figures available are third party directory listings, where this category spans under $25 to $149 an hour with 13 of 20 vendors sitting in the $50 to $99 band.
Who owns the model after a generative AI development company builds it?
Whatever your contract says, and none of the eight vendor pages we read said anything at all. A generative AI build produces fine tuned weights and adapters, a system prompt library, an evaluation set, a retrieval index with its chunking configuration, and often synthetic training data. None of those are source code, so a standard work product clause may not clearly transfer them. Name each artifact explicitly.
What is included in generative AI development services?
In practice five things: use case selection and feasibility, data access and retrieval engineering, the application layer that wraps the model, an evaluation harness that proves the output is good enough, and production operations covering cost, latency and monitoring. The model call itself is the smallest piece. Most of the budget goes to data plumbing and evaluation, which is why quotes vary so much.
What is the difference between generative AI development services and LLM development services?
In vendor marketing, almost nothing. LLM development services usually signals text and language work such as retrieval augmented generation, chat assistants and fine tuning. Generative AI development is the broader label that also covers image, audio, video and code generation. Buy on the specific artifact you need built, because the two labels are sold by the same teams.
Is a US based generative AI development company more expensive?
Not reliably. In the 20 vendor directory listing we checked, two Virginia firms list $25 to $49 an hour while two Polish firms list $50 to $99, and the single highest band, $100 to $149, belongs to a company in Austin, Texas. A US address in this category predicts the sales entity, not the rate and not where the engineers sit.
What is the minimum budget for a generative AI project?
Directory minimums for this category run from $1,000 to $50,000 and up, with 8 of 20 vendors setting $10,000 and 5 setting $25,000. Below roughly $10,000 you are buying a prototype, not a production system. If your budget is under that, hire individual senior specialists directly rather than an agency, because agency overhead consumes a fixed share regardless of project size.
How do I compare quotes from generative AI development companies?
Convert every quote into engineer months. Divide the price by the rate the vendor would charge, then by 160 hours. A $100,000 quote at $74.50 an hour is 8.4 engineer months. Once every proposal is expressed that way you can see which vendor is pricing more work and which is pricing more margin, which a raw dollar figure hides completely.
Should I hire a generative AI development company or individual developers?
Hire a company when you need a coordinated team, an inherited compliance posture, or accountability for an outcome rather than for hours. Hire individual senior specialists when you already know the workflow, the systems it touches and how you will judge success, because then you are buying delivery capacity and agency overhead adds an account manager and a sales function on top.
How long does a generative AI project take?
The published bands imply 0.4 engineer months at the cheap end and about 42 at the top. A realistic first production feature sits near 400 to 950 hours, which is one senior engineer for roughly three to six months or a pair over two to three. Appinventiv publicly quotes 3 to 6 months for an MVP and 12 months and up for enterprise scale, which matches that arithmetic.
What should be in a generative AI development contract?
Name the delivery country per engineer, assign fine tuned weights, adapters, prompts, evaluation sets, retrieval indexes and synthetic data to you on payment, state which model providers may be used and whether your data can train them, set an accuracy threshold measured on an agreed evaluation set, and require handover of repositories and infrastructure access within a fixed number of days.
Do I need a generative AI consulting company before I build?
Only if the use case is genuinely undecided. Consulting earns its fee when the hard question is what to build and whether the data supports it. If you already know the workflow and the success measure, a discovery phase mostly rediscovers what you told it, and the money is better spent on a small paid pilot that produces a working artifact and a real accuracy number.
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