Services
AI Development Services Built for Production
Our AI development services cover AI agents, generative AI, automation, machine learning, data engineering, integrations, custom AI software, and consulting. Each service has a clear scope and a fixed quote before development starts.
- First step, depending on the service
- 1–4 weeks
- The smallest first build
- From $8k
- Build quote, agreed before work starts
- Fixed
- Code, prompts and models at handover
- Yours
Where the work runs
The systems our AI development services connect to
SalesforceCRM
HubSpotCRM
ServiceNowService desk
ZendeskHelp desk
ERP
NetSuiteERP- SalesforceCRM
- HubSpotCRM
- ServiceNowService desk
- ZendeskHelp desk
- ERP
- NetSuiteERP
WorkdayHR
SlackMessaging
Microsoft TeamsMessaging
SnowflakeWarehouse
DatabricksLakehouse
Payments- WorkdayHR
- SlackMessaging
- Microsoft TeamsMessaging
- SnowflakeWarehouse
- DatabricksLakehouse
- Payments
The services
Our AI development services, and the problem each one solves
Compare prices and timelinesChoose among our AI development services by the problem in front of you rather than by the technology. Each card says what the service delivers, and its page shows how we build it, what it costs and what you keep.
- Explore AI agent development
AI agent development
Agents that finish real tasks inside your CRM, help desk or ERP, using only the tools you approve, and pass anything outside that list to a named person.
- Explore generative AI development
Generative AI development
Assistants that answer from your own documents, quote the passage behind each answer and say plainly when the material does not cover the question.
- Explore AI consulting
AI consulting
A readiness assessment, a strategy or a proof of concept that ends in a written decision on what to build first, including what is not worth building.
- Explore AI automation
AI automation
Workflows where routine cases go straight through and every case the system holds back lands with a person, together with why it was held.
- Explore custom AI development
Custom AI development
Software, an app or an MVP built to acceptance conditions you sign before the work starts, with the code and models in your own accounts.
- Explore machine learning development
Machine learning development
Forecasts, scores and detections trained on your own history, and released only once they beat the method your team relies on now.
- Explore data engineering
Data engineering
Pipelines, warehouses and data contracts that turn late, scattered or untrusted data into something agents, models and reports can rely on.
- Explore integrations
Integrations
Connectors that let AI read from and write to the platforms you already run, each on the smallest set of permissions that does the job.
Compare
AI development services compared: price range, timeline and first step
The ranges are build costs for each of our AI development services, set by the weeks of work and the size of the team. Model, hosting and cloud costs are modelled at your volume and quoted separately. Every service opens with a first step that settles scope and price before anything is built, and where that step carries a fee, the fee is credited against the build.
| Service | The problem it fits | First step | Price range | Timeline |
|---|---|---|---|---|
| AI agent development | Work a person does by hand across your CRM, help desk or ERP. | A two-week scope, ending in a fixed quote. | Pilot $8k–$35k · production agent $16k–$82k · managed run $9k–$25k a month | Pilot 4–6 weeks · production 8–14 weeks |
| Generative AI development | Answers your team digs out of policies, tickets or manuals. | A two-week scope, ending in a fixed quote. | Scoped pilot $8k–$35k · production system $12k–$59k | Pilot 4–6 weeks · production 6–10 weeks |
| AI consulting | Not yet knowing what to build first, or whether to build at all. | Readiness assessment: 2 weeks, $4k–$12k, credited against the build. | Strategy $6k–$24k · proof of concept $8k–$35k · managed support $9k–$25k a month | Strategy 3–4 weeks · proof of concept 4–6 weeks |
| AI automation | A high-volume workflow with many manual touches. | Workflow review: 1 week, ending in a fixed quote. | One workflow $10k–$53k · a workflow family $16k–$82k · managed run $9k–$25k a month | Working version 3–6 weeks, then 1–2 weeks beside your team |
| Custom AI development | A need no product covers, where you want to own the code and the model. | A one-week scope with written acceptance conditions. | MVP from $8k · application from $12k · enterprise platform from $26k | Feasibility 1–2 weeks · working version 3–6 weeks |
| Machine learning development | A forecast, a score or a detection from your own history. | Feasibility sprint: 3–4 weeks, $6k–$24k, credited against the build. | One model in production $20k–$94k · MLOps platform $12k–$59k | Production model 10–16 weeks · MLOps 6–10 weeks |
| Data engineering | Data that arrives late, cannot be trusted or sits in too many places. | Assessment and architecture: 2–3 weeks, $4k–$18k, credited against the build. | AI-ready data layer $12k–$59k · platform build or migration $26k–$153k · dedicated team $9k–$25k a month | Data layer 6–10 weeks · platform or migration 3–6 months |
| Integrations | AI that has to read from or write to systems you already run. | A signed scope list: the objects read, the write scopes and the auth model. | One system $8k–$35k read plus draft, $16k–$82k scoped write · two to four systems $26k–$153k | Read plus draft 4–6 weeks · scoped write 8–14 weeks |
How an engagement works
How our AI development services run, from the first call to handover
The services differ in what gets built, not in how the work runs. Every engagement moves through the same four stages, and you can stop at the end of any of them with what has been delivered so far.
Scope
We learn the problem, the systems it touches and how success will be measured. The stage ends with a written scope, a fixed quote for the build and the name of the engineer who would do the work, and any fee for it is credited against that build.
You get
Written scope, fixed quote, named engineer
Typical duration1–4 weeks, by service
Prove
A narrow version runs on your data and is judged against a test set agreed before it was built. If it falls short, you find out here, at the lowest cost of the whole engagement.
You get
A working pilot and its measured result
Typical duration3–6 weeks
Build
The production system takes shape: connectors, monitoring, approval gates and runbooks. Each release has to pass the same tests as the pilot before it ships.
You get
Production system, tests and runbooks
Typical duration6 weeks to 6 months, by service
Run
Your team takes over with training and the runbooks, or we keep it running as a managed service. Whichever you pick, the code, prompts, models and test sets remain yours.
You get
A handover, or a managed service
Typical durationOngoing
AI agents
The jobs an agent can take off your team
An agent is the part of our AI development services built around one job and one owner. Pick a function to see what the agent takes on and the point where a person steps in.
Sales agents
Picks up each new lead, researches the account, checks the fit against your ideal customer profile and proposes meeting times, leaving price and terms to a rep.
Takes on
- Account research before the first reply
- Fit checks against your customer profile
- Meeting proposals and CRM notes
Connected to
- HubSpot
- Salesforce
- Microsoft 365
Customer service agents
Answers order, billing and account questions from your policies, completes refunds and changes inside the limits you set, and passes the case to a person, history attached, when it falls outside them.
Takes on
- Order and billing questions
- Refunds and changes inside set limits
- Hand-offs with the full history
Connected to
- Zendesk
- Shopify
- Stripe
Voice agents
Takes calls when your team cannot, books or moves appointments, collects the details a person will need and transfers the caller whenever they ask for someone or the call needs judgement.
Takes on
- Calls outside office hours
- Bookings and reschedules
- Warm transfers with a summary
Connected to
- Twilio
- Google Workspace
- HubSpot
Finance agents
Reads supplier invoices, matches them to the purchase order and the goods receipt, posts the clean ones for approval and sends each mismatch to accounts payable with the reason.
Takes on
- Invoice reading and coding
- Matching to orders and receipts
- Mismatches routed with the reason
Connected to
- NetSuite
- SAP
- Microsoft 365
HR agents
Answers staff questions from your handbook and policies, starts the onboarding checklist for each new hire and drafts letters and leave records for HR to sign off.
Takes on
- Policy answers with the source
- Onboarding checklists
- Letters and leave records
Connected to
- Workday
- Slack
- Google Workspace
Legal agents
Reads contracts against your playbook, marks the clauses that depart from it and drafts a suggested change for each, leaving every decision to a lawyer.
Takes on
- Playbook checks on each contract
- Clause flags with the reference
- Suggested redlines for review
Connected to
- Microsoft 365
- SharePoint
- Slack
Case studies
Results from our AI development services
- Small business lending · AI agent developmentNext action on an application in 18 to 24 hours, down from 48, in trial usageMerchants, funders and sales reps ask one agent about an application, and each sees only their own part of it. Offers stay inside set limits, and a rep takes over when a conversation turns difficult.Read the case study
- Web3 data · Data engineeringLive transactions taken in with few or no stops, and a growing history that stays quick to queryTransactions, wallet activity and contract events arrive through a queue as they happen and are written to an index of the whole chain, ready to query.Read the case study
- Wildlife monitoring · Custom AI and machine learningAverage station set-up under 10 minutes, down from nearly 25 to 30Listening stations name birds from live field audio with adapted BirdNET models, and the client's own customers install them from a mobile app with no technical set-up.Read the case study
Industries
Where our AI development services start, industry by industry
The services are the same in every sector; the first project is not. Pick an industry to see where a first project usually begins and which service each starting point uses.
AI for insurers
Carriers, MGAs and brokers tend to start where documents pile up: policy changes, first notice of loss and the underwriting file. The rules behind each decision stay with your underwriters.
Where clients start
- AI agent development: policy changes and endorsements
- AI automation: first notice of loss intake
- Generative AI: answers from policy wordings
- Machine learning: fraud and anomaly scores
- Data engineering: one record per policyholder
AI for banks
Banks usually begin with work that model risk and vendor review can assess clearly: servicing questions, KYC files and alert triage, each with an audit trail from the first release.
Where clients start
- AI agent development: servicing and dispute intake
- AI automation: KYC file assembly
- Generative AI: answers from product terms for advisers
- Machine learning: fraud and credit scoring
- Data engineering: lineage your regulator can follow
AI for healthcare providers
Providers and payers start with access and paperwork rather than clinical decisions: scheduling, eligibility, prior authorisation and claims follow-up, with patient data kept inside your boundary.
Where clients start
- AI agent development: scheduling and reminders
- AI automation: prior authorisation packets
- Generative AI: answers from protocols and payer rules
- Machine learning: no-show and demand forecasts
- Data engineering: permissions that follow the record
AI for manufacturers
Plants start where downtime and rework cost the most: inspection on the line, maintenance planning and the paperwork around suppliers and quality, without writing to the control layer.
Where clients start
- Machine learning: visual inspection and failure prediction
- AI automation: supplier and quality documents
- AI agent development: quote preparation and supplier follow-up
- Generative AI: answers from work instructions
- Data engineering: plant and ERP data in one model
AI for supply chain teams
Planning and procurement teams begin with the exceptions that fill their week: late orders, short supply and replenishment calls that depend on data from several partners.
Where clients start
- Machine learning: demand forecasts at order level
- AI agent development: supplier follow-up and exceptions
- AI automation: purchase order to invoice matching
- Data engineering: partner data in one shape
- Integrations: ERP and planning systems connected
AI for logistics firms
Carriers, brokers and 3PLs start with the documents and messages a shipment generates: delivery notes, customs paperwork, check calls and customer updates.
Where clients start
- AI automation: bills of lading and proof of delivery
- AI agent development: check calls and customer updates
- Machine learning: arrival time prediction
- Integrations: carrier and visibility platforms
- Generative AI: answers from tariffs and contracts
AI for retailers
Retailers start with the volume that peaks every season: customer messages, returns, product data and the forecasts that decide what gets reordered.
Where clients start
- AI agent development: order, return and refund requests
- Machine learning: replenishment forecasts and ranking
- Generative AI: product data and customer answers
- AI automation: supplier invoices
- Data engineering: one view of stock and sales
AI for construction firms
Contractors and owners start with the documents a project produces: bids, RFIs, submittals and change orders, spread across systems that rarely share a record.
Where clients start
- AI automation: RFI and submittal routing
- Generative AI: answers from drawings and specifications
- AI agent development: bid document review
- Custom AI development: a shared project record
- Machine learning: equipment maintenance forecasts
FAQs
Questions buyers ask about AI development services
Straight answers on cost, timelines, where to start, what is included and who owns the work.
How much do AI development services cost?
It depends on the service and the shape of the work. A pilot or proof of concept usually costs $8k–$35k. A first production system ranges from about $10k to $94k, depending on the service, and larger builds, such as a whole function or a platform migration, run $26k–$153k. Managed operation is $9k–$25k a month. The comparison table sets each service's ranges side by side, and the quote is fixed at the end of the first step.
How long do AI development services take?
The first step takes one to four weeks, depending on the service. A pilot usually follows in four to six weeks, a production system in six to sixteen weeks, and a data platform build or migration in three to six months. Each service page gives its own schedule, and the timeline column above shows them together.
Which of your AI development services should we start with?
Start from the problem rather than the technology. If people spend their day moving work between systems, look at agents or automation; if the answers are buried in documents, generative AI; if you need a prediction from your own history, machine learning. If you are still unsure, the readiness assessment exists for exactly that question.
What is included in your AI development services?
The build itself, the connectors to your systems, an evaluation suite agreed before the build starts, monitoring, approval gates where the work calls for them, and runbooks. The code, prompts, models, evaluation sets and dashboards are yours at handover, in your own repositories and cloud account.
Can these services work inside the software we already use?
Yes. Most of the effort in any of our AI development services goes into connecting to what you already run: CRM, help desk, ERP, data platform, telephony and document stores. Each connector gets the narrowest access that does the job, and you hold the credentials, so you can revoke them without involving us.
Which AI models do you build with?
Claude, OpenAI, Gemini, Llama or Mistral, chosen per task on accuracy against your own test set, then speed and cost. Where data cannot leave your boundary, we run open-weight models in your cloud or on your hardware. The choice is written into the scope.
Who owns what you build?
You do. Code, prompts, model weights, evaluation sets and infrastructure definitions sit in your repositories and cloud account, and nothing in the design needs us in order to keep running.
How do AI development services compare with building in-house?
In-house is often the right long-term answer. An outside team helps when you need the first system in production sooner than you can hire for it, or when nobody on staff has shipped this kind of work before. We can build the first one with your engineers alongside, so the next one is theirs.
What happens once the system is live?
You choose. Your team takes it over with training and runbooks, or we run it as a managed service for $9k–$25k a month, covering monitoring, test reruns after every model or prompt change, tuning and fixes. The system stays yours whichever you pick.
Tell us the problem. We will tell you which service fits.
Describe the work, the systems it touches and what a good result would look like. An engineer replies within two business days with the service we would start with, its first step and the price range that applies.