AI development companies · Technology
Speak to the founder who wants one AI feature that works, not an AI strategy deck.
The owner of a Chennai insurance brokerage gets a heap of policy documents every week, and two staff retype them into an insurer's portal. A nephew shows the owner a chatbot demo and says AI can do this.
Scope, fee, reporting and term are agreed in writing after we have read your brief and spoken to you.
In one paragraph
AI development companies build assistants, document readers, voice agents and vision systems for clients. Marketing sets real, scoped use cases apart from hype, which careful buyers look for. Sales turns a proof of concept into a production contract. That is slow work. GullySales works on the use-case pages, the proof-of-concept offer and the answers a client's IT head will ask for.
The owner searches for companies that build it, finds page after page of the same words, and cannot tell which firm has built something that survived a month of real, messy scans. Buyers have heard every promise. A firm that says what the first version will not do, and what it costs to find that out, stands apart, provided it says so without sounding nervous.
Last updated 18 Oct 2026.
How buyers decide
How AI development companies are chosen.
Buyers choose a use case before a company. They want to read invoices, answer customer queries on WhatsApp, summarise calls, check product photos or forecast a number. A firm with a clear page for that use case, plus a plain note on how accuracy is measured and what a person still checks, gives the buyer something to take to colleagues.
A small proof of concept is the usual first step. The buyer wants a fixed scope on their own sample data, a plain account of what success means, and a stopping point if the results are poor. A firm that will not describe failure leaves the buyer to imagine it.
Questions on data and cost follow quickly: where the data goes, which model provider is used, whether it can run inside the client's own systems, and what the running costs are once it is live. Data protection rules differ and change, so buyers want a calm answer and a pointer to their own legal adviser for specifics.
The problem
What usually goes wrong for AI development companies.
What owners tell us on the first call, in their words.
“Everyone claims AI and buyers have stopped believing it”
Our website says intelligent automation and next-generation solutions, and the owner closes the tab.
“Proofs of concept work and production does not follow”
The demo impresses, but nobody scoped what happens when real documents arrive messy, and the client loses interest.
“Buyers expect a magic number for accuracy”
They ask what percentage will be right, and we cannot answer honestly without seeing their data.
“We lose to a freelancer with a cheap chatbot”
The comparison is price, because we have not explained the difference between a demo and something that keeps working.
“Sales cycles stall at the data question”
The client's IT head or lawyer asks where information goes, and the answer takes weeks.
“Our best work is confidential”
Clients do not want it known that they use AI at all, so we cannot publish the projects we are proudest of.
What we do
What we do for AI development companies.
Everything included for AI development companies.
Use-case pages
A page for each thing buyers ask for, such as reading invoices, answering customer queries or checking photos, with what the system does, what it cannot do, and where a person still checks.
A proof-of-concept offer
A written description of a first project: the sample data needed, what will be built, how success is judged and where it stops if the result is not good enough.
An honest accuracy note
A plain page that explains why accuracy depends on the buyer's own data, what is measured on the sample and what review step remains after launch.
Data and model questions sheet
A short document answering where data is held, which model providers are used, what can run inside the client's systems and what is deleted, checked by your own adviser.
Confidential case stories
Write-ups by problem and industry, such as a document backlog at an insurance broker, with the client unnamed and the figures left out unless approved.
Production handover plan
A description of what happens after the proof of concept, including monitoring, retraining of the client's staff and what happens when the first version meets messy data.
How the result is measured
- Enquiries by use case
- Proof-of-concept proposals sent
- Proofs of concept signed
- Proofs that move to production
- Partner-sourced projects
- Data questions from clients and how they were answered
Recorded as a baseline before work starts, so every later report has an honest comparison.
Every service, written for AI development companies
Each has its own page: what it involves for AI development companies, what you get, and what it is measured on.
- Lead generationBring in enquiries from buyers who already have one task they want automated.
- SEOGet found by the buyer who searches for the task, not for the technology.
- Social media marketingShow your working on social media, because buyers trust a build they can watch.
- Content marketingPublish what you have learned from real builds, and buyers will read it before they call.
- Buyer personasWrite for the sponsor, the IT head and the user, because each decides a different part.
- CRMKeep a record of each enquiry from first question to a running system.
- Follow-up systemsFollow up after the demo, because the project is decided in the weeks that follow it.
- WhatsApp marketingUse WhatsApp for quick questions, shared samples and clear next steps.
- Digital marketingChoose a few channels that suit a long, careful sale, and run them properly.
- WebsiteMake the website say what you have built, what it cannot do and what to do next.
Worth a page and a campaign of their own
Pages for specific use cases · Honest scoping and accuracy language · Small proof of concept with a stopping point · Clear answers on data location and model use · Production handover and monitoring · Confidential case stories · Comparison with cheap chatbots and freelancers · Staff training for the client team
Priority campaigns
Campaigns for what AI development companies most want to sell.
Each one planned around when your buyers decide, and measured against the baseline.
Use-case searches
Pages and ads for terms such as invoice data extraction, WhatsApp AI assistant for business, call summarisation and quality inspection with cameras.
Founder and operations head outreach
Short, specific messages to owners and operations heads at firms with obvious document or query backlogs.
Live build sessions
Webinars and meetup talks in which one small system is built from a sample document set, showing what works and what failed.
Partner referrals from software and consulting firms
Contact with software houses and consultants who get AI requests they do not want to build themselves.
Beyond search
Where we reach buyers of AI development companies, beyond Google.
Search matters, but it is rarely the only way this industry's buyers find a supplier.
Founders and operations heads with paper backlogs
Insurance brokers, logistics firms, finance back offices and hospital billing desks all sit on visible document or query volumes. Outreach to them names one backlog, not AI in general.
Customer support leaders
A support head sees the same ten questions arrive on phone and WhatsApp. An approach that starts from that queue gets read; one that starts from the model does not.
CTOs and IT heads
The person who signs off data handling reads a different document from the sponsor: where data goes, which model provider sees it, what stays inside the client's network.
Software houses and consultants
ERP partners, web agencies and BPO firms get AI requests they would rather pass on. A note saying which requests suit you gives them somewhere to send them.
Startup founders and incubators
Incubator cohorts ask what a first AI feature takes. A session built on worked examples of document and query tasks answers that, and brings the founders who have a real task.
Who it is for
This is written for these AI development companies.
- Conversational AI and WhatsApp assistant builders
- Document reading and data extraction specialists
- Voice agents and call analysis providers
- Computer vision firms for factories, retail and security
- Recommendation and forecasting model builders
- Generative AI application developers for enterprise teams
- AI consultants who build proofs of concept for startups
- Agent and workflow automation builders
Not for
It is not the right fit if.
- You want a guaranteed Google ranking or a guaranteed number of leads. Nobody honest can promise either.
- You need enquiries by next week and have nobody to answer them.
- You want posts and reach reported, not enquiries and orders.
How it works
How the work runs for AI development companies
The work itself, in order. How an engagement starts, from your brief to a written scope, is set out on our method page.
- 1
Pick the use cases you have shipped
What you have built is reviewed, and the use cases where you can show evidence and state plain limits are chosen.
- 2
Write without hype
The site is rewritten in plain words: what works, what needs a person, what you will not promise.
- 3
Package the first project
A proof-of-concept offer and the data questions sheet, shaped so the sponsor and the IT head can each approve their part.
- 4
Go where problems are discussed
Live sessions, partner contacts and search pages, each built around one of the chosen use cases.
- 5
Carry proofs to production
A plan for the conversation that follows each proof of concept, and a record of which ones became live systems.
Where this fits
Three pieces of sales work, in this order.
GullySales builds every engagement from three pieces of sales work. This page is not one of them, but the same three steps apply to the business behind it.
Step 1
Sales audit
Find where deals are being lost and what to fix first.
Start here if you cannot say where orders are lost.
Step 2
Sales process design
One written way to sell, from first enquiry to repeat order.
Start here if every salesperson sells differently.
Step 3
Sales management
A target, a review routine and someone who owns the number.
Start here if the team has targets and no routine.
FAQ
Questions AI development companies ask before they call.
Not here? More answers, or ask on WhatsApp.
Can you write that our system is highly accurate?
How do we compete with cheap chatbot sellers?
Will you write about AI and data protection law?
We are a two-person team. Is this worth it?
How is this different from marketing data analytics companies?
How much does it cost?
How long is the contract?
How soon will we see results?
Who will actually do the work?
What do you need from us?
Part of Technology. See the other industries in the sector.
Your next practical step
Tell us what you are trying to grow, and we will read it before we call.
Eight short steps, mostly taps. Skip anything you would rather answer on the call.