AI Development Company for AI Agents and Automation
We design, build, and run AI agents, generative AI systems, and automation inside the tools your teams already use. We scope one workflow in two weeks, validate it on your data, and give you a fixed quote and named engineer before development starts.
- 6
Years in AI
- 30+
AI engineers
- 97%
Average Eval Score
- 8
Industries covered
The AI build stack
AI Models, Platforms and Frameworks we build on
OpenAIFoundation models
Foundation models
AWS BedrockModel platform
Agent orchestration
Copilot StudioAgent platform
Hugging FaceModel hub- OpenAIFoundation models
- Foundation models
- AWS BedrockModel platform
- Agent orchestration
- Copilot StudioAgent platform
- Hugging FaceModel hub
OllamaLocal inference
Inference server
GeminiFoundation models
Vertex AIML platform
Mistral AIOpen models
LlamaIndexRAG framework- OllamaLocal inference
- Inference server
- GeminiFoundation models
- Vertex AIML platform
- Mistral AIOpen models
- LlamaIndexRAG framework
What we do
What Our AI Development Company Builds
We build AI agents, generative AI and automation that work inside the systems your teams already use. They read documents, follow business rules and complete real work, from CRM updates and bookings to invoice processing. AI consulting, readiness assessments and proof of concept projects help define what to build first. Every engagement starts with one workflow and a two-week scope, followed by a fixed quote, tested delivery and full handover of the code, prompts, evaluation sets and runbooks.
Documents in
- Form
Inside your systems
- Reads documents
- Follows business rules
- Completes tasks
Tasks done
- CRM updated
- Booking made
- Invoice processed
- Scope
- One workflow, one owner
- One business owner on your side approves write access, resolves decisions and has the authority to stop the work.
- Quote
- Fixed after scope
- We set the price at the end of the two-week scope, so the agreed build does not change price halfway through.
- Proof
- Eval gate, every release
- We test every release against your own records and an agreed threshold. Only the version that clears it ships.
- Ownership
- Yours at handover
- You receive the code, prompts, evaluation sets, dashboards and runbooks, plus the training to run the system.
Services
Services for Every Stage of an AI Build
Get a fixed quoteEight services, one delivery model. Every build connects to your systems, ships with an evaluation suite and starts with a published price range.
- Explore AI Agent Development
AI Agent Development
AI agents complete workflows in sales, support, finance, HR, legal, insurance and voice, with clear tools, limits and human approval.
- Explore Generative AI Development
Generative AI Development
RAG systems, chatbots and knowledge assistants answer from your data, cite the source and flag responses the evidence does not support.
- Explore AI Consulting
AI Consulting
Readiness assessments, strategy, proofs of concept and implementation plans show what to build first, what it will cost and what to delay.
- Explore AI Automation
AI Automation
Workflow, document and invoice automation completes routine work automatically and sends exceptions to people with the reason for review.
- Explore Custom AI Development
Custom AI Development
Bespoke software, applications and MVPs turn specific business requirements into production-ready systems when standard tools fall short.
- Explore Machine Learning
Machine Learning
Forecasting, fraud detection, computer vision, and recommendation models use classical ML, with MLOps to maintain performance.
- Explore data engineering
Data Engineering
Pipelines, warehouses and vector stores give AI systems clean, reliable data, with contracts and quality tests that keep that data trustworthy.
- Explore integrations
Integrations
Connect AI agents to Salesforce, HubSpot, Zendesk, ServiceNow, SAP and 15 more platforms, with clear documentation of what each agent reads and writes.
AI agents
AI Agents by Function
One agent, one job, one owner. Choose a function to see the work it completes and the systems it uses.
Sales Agents
Works inbound leads from first touch to booked meeting: enriches the account, scores it against your ICP, drafts the reply and logs the outcome, with reps approving anything outside its brief.
Handles
- Lead enrichment and ICP scoring
- Reply drafts and follow-ups
- Meeting booking and CRM hygiene
Works inside
- Salesforce
- HubSpot
- Google Workspace
- Slack
Marketing Agents
Turns one campaign brief into segmented, on-brand variants, schedules approved content and reports performance, with a marketer signing off before anything goes live.
Handles
- Campaign variants and copy drafts
- Audience segmentation
- Performance reporting
Works inside
- HubSpot
- Google Workspace
- Slack
Customer Service Agents
Resolves routine billing, account and order tickets, then sends unclear cases to a person with the full context attached.
Handles
- Ticket triage and classification
- Refunds and changes within policy
- Drafted replies with sources
Works inside
- Zendesk
- Intercom
- Stripe
- Shopify
Voice Agents
Answers calls, books and reschedules appointments, qualifies leads and hands over when the caller or policy calls for a person.
Handles
- Inbound call handling
- Appointment booking
- After-hours coverage
Works inside
- Twilio
- Google Workspace
- Salesforce
Finance Agents
Captures invoices, completes the three-way match, posts approved records and writes the audit trail, so accounts payable reviews exceptions instead of every document.
Handles
- Invoice capture and three-way match
- AP and AR follow-ups
- Reconciliation prep
Works inside
- NetSuite
- SAP
- Stripe
HR Agents
Answers policy questions from your handbook, runs onboarding checklists and prepares leave and letter requests, with HR reviewing exceptions.
Handles
- Policy answers from your handbook
- Onboarding checklists
- Leave and letter requests
Works inside
- Workday
- Microsoft 365
- Slack
Legal Agents
Reviews contracts first, traces every flag to the relevant clause and gives lawyers a faster starting point for decisions.
Handles
- Contract review and redlines
- Clause extraction
- NDA intake triage
Works inside
- Microsoft 365
- Google Workspace
- Slack
Insurance Agents
Supports policyholders and brokers with quotes, endorsements and first notice of loss, with carrier rules controlling what it completes without approval.
Handles
- Quote intake and data prefill
- Endorsement processing
- FNOL capture and routing
Works inside
- Salesforce
- Twilio
- Microsoft 365
Underwriting and claims agents
Assembles the file, checks the rules and drafts the decision with its rationale, so underwriters review instead of building the case from scratch.
Handles
- Document intake and extraction
- Rule and risk checks
- Decision drafts with rationale
Works inside
- Guidewire
- Snowflake
- Microsoft 365
Due Diligence Asgents
Reviews the data room and gives analysts document summaries, company and market briefs, and red-flag lists with page references attached.
Handles
- Data-room document review
- Company and market briefs
- Red-flag summaries with references
Works inside
- Microsoft 365
- Google Workspace
- Snowflake
How we work
How our AI Development Process Works
Start with one workflow and see it working on your data before committing to the full build. Weekly demos keep progress visible at every stage.
Scope
We map the workflow, the systems it touches and the metric that defines success. You get a clear plan, a fixed quote and the name of the engineer who would build it before deciding whether to continue.
You get
Use-case brief, integration map, fixed quote
Typical duration2 weeks
Prove
We build a working pilot on your real data in a sandbox and demo it weekly. The evaluation set defines success before the build starts, and the pilot has to clear that bar before moving forward.
You get
Working pilot, evaluation set, go or no-go
Typical duration4–6 weeks
Build
We turn the pilot into a production system with write integrations, guardrails, admin tools, monitoring and release gates. Every change runs through the evaluation suite before deployment.
You get
Production system, release gates, runbooks
Typical duration8–14 weeks
Run
We roll out with cost controls and human approval for write actions until the agreed gate is cleared. You can take over with full handover and training or keep us on through a managed service. You own the system either way.
You get
Dashboards, training, handover or managed service
Typical durationOngoing
Runs inside your stack
Salesforce
HubSpot
Zendesk
Intercom
ServiceNow
Jira
Slack
Microsoft Teams
NetSuite
Workday
Snowflake
Databricks
BigQuery
Shopify
Twilio
Case studies
AI development work with measurable results
- Service businesses · Voice agentFirst response to a new lead: 2 to 6 hours down to under 1 minuteA voice agent makes first contact with every new enquiry by call, WhatsApp, SMS or email, writes the summary and routes the lead to a rep, who takes over the sales conversation.Read the case study
- Optician training · Role-play with an AI patientAverage role-play session: about 25 minutes down to under 15Opticians practise consultations on an AI patient. 85 to 92% of consultation stages are identified correctly in common scenarios, and feedback runs on a separate model to keep the running cost down.Read the case study
- Healthcare · Provider credentialingProvider onboarding: 2 to 4 weeks down to about 1 to 2Invitations, documents and status updates run as one tracked workflow, with 30 to 45% fewer manual follow-ups. The file review stays with the credentialing team.Read the case study
Industries
AI development by industry
The technology changes less than the rules around it. Choose an industry to see the first practical applications and the controls the work demands.
AI in insurance
Policy servicing, first notice of loss and underwriting file assembly for carriers, MGAs and brokers. Each drafted decision shows its rationale, so underwriters review the case instead of assembling it.
What ships first
- Policy servicing agents
- FNOL and claims triage
- Underwriting document intelligence
- Voice agents for service and sales
- Fraud and anomaly detection
AI in banking
Service agents, fraud models and KYC document intelligence for retail, commercial and private banks, designed with model-risk review and vendor governance in mind from the start.
What ships first
- Customer service agents
- Fraud and anomaly detection
- KYC, AML and onboarding document intelligence
- Finance operations agents
- Banker and adviser knowledge assistants
AI in healthcare
Agents support patient access, documentation drafts, prior authorisation and revenue-cycle work, with clinician approval where required and PHI controls built into the design from the start.
What ships first
- Patient access and scheduling voice agents
- Clinical documentation support
- Prior authorisation and claims document intelligence
- Revenue-cycle workflow automation
- Knowledge assistants for policies and protocols
AI in manufacturing
Visual inspection, planning models and maintenance forecasts support plant operations, with procurement and document automation for the back office and controls for OT, IT and safety.
What ships first
- Visual quality inspection
- Predictive maintenance
- Demand and production planning
- Invoice and back-office automation
- Supplier document processing
AI in supply chain
Forecasting, replenishment and exception handling support planning, procurement and logistics, with the data and integrations needed to move from prediction to action.
What ships first
- Demand forecasting
- Inventory and replenishment workflow automation
- Supplier and procurement agents
- Logistics document automation
- Invoice and settlement automation
AI in logistics
Shipment exception agents, freight document automation and load planning help carriers, 3PLs, forwarders and shippers manage work inside a live network.
What ships first
- Shipment exception agents
- Freight document automation (BOL, POD, customs)
- Carrier and customer voice agents
- Invoice and settlement automation
- Warehouse computer vision
AI in retail
Recommendations, forecasting and service agents support online, store and omnichannel operations, with privacy, brand safety and measurement built into the rollout.
What ships first
- Personalisation and recommendations
- Demand forecasting and replenishment
- Customer service agents
- Marketing content agents
- Returns and fraud detection
AI in construction
Bid review, RFI and submittal processing, and change-order automation help contractors and owners move faster through document-heavy work and fragmented project data.
What ships first
- Bid and tender document review
- RFI and submittal workflow automation
- Site safety computer vision
- Equipment predictive maintenance
- Invoice and change-order automation
Security
The security questions, answered before the call
Security becomes critical as soon as AI can write to a system of record. We define the access scope, service-account model and revocation path before implementation so the review starts with clear controls.
Every connector uses credentials you control inside your cloud account, and your team can revoke access directly.
| Question | Answer |
|---|---|
| Where does our data go? | It stays inside your boundary. Documents and records are processed in your cloud account or a private deployment you approve; nothing is copied to a Meronym environment to train or tune a model. |
| Which models, hosted where? | Claude, GPT-5, Gemini, Llama or Mistral, chosen per task. Through public APIs where your policy allows, otherwise private deployments on AWS Bedrock, Azure OpenAI or Google Vertex AI, or on your own hardware. |
| Who can see what the system does? | Every action is logged: actor, inputs, outputs, timestamp and the reasoning trace, retained to your policy and queryable by case. Your team reads the log; so does your auditor. |
| What can it write? | Only the scopes on the connector sheet, agreed in writing before build. Anything outside them fails closed rather than degrading, and write actions run behind an approval gate until the evaluation gate clears. |
| Can we switch it off? | Yes, unilaterally, from your side. Credentials live in your secret manager; revoking them stops every connector without anyone at Meronym in the loop. |
| What compliance do you build to? | We build to GDPR and to HIPAA-ready patterns: data minimisation, PII classified at ingestion and redacted where policy requires, audit trails and retention you set. |
FAQs
Common Buyer Questions
Clear answers on cost, timelines, models, systems and what happens after launch.
How much does AI development cost?
A pilot on one workflow runs $8k–$35k over 4–6 weeks. A production system runs $16k–$82k to build over 8–14 weeks, plus a run cost modelled at your expected usage. A managed service runs $9k–$25k a month. Each service page shows its own ranges, and the quote is fixed at the end of scope.
How long does an AI development project take?
Two weeks to scope, about four to six weeks for a working pilot on your data, and eight to fourteen weeks for production, depending on how many systems the agent writes to. Voice and regulated workflows sit at the long end of the range.
Do you work with the systems we already run?
Yes; that is most of the job. We build least-privilege connectors to your CRM, helpdesk, ERP, data platform and telephony, and publish what each one reads and writes. The platforms we connect to are listed on the integrations page, and a custom connector is a priced item, not a surprise.
Which AI models do you use, and where do they run?
Whichever fits the task: Claude, GPT-5, Gemini, Llama or Mistral, through public APIs or private deployments on AWS Bedrock, Azure OpenAI or Google Vertex AI. We choose per task on accuracy, latency, cost and where your data is allowed to live, and the choice is written into the scope.
What happens after launch?
Either a handover with runbooks and training for your team, or a managed service that covers monitoring, evaluation reruns on every model or prompt change, tuning and upgrades under an SLA. You own the code, the prompts and the evaluation sets in both cases.
How do you stop the system doing the wrong thing?
Three mechanisms. A typed tool list, so the agent can only do what its tools allow. An escalation table: the conditions that stop it and who picks up. And approval gates on write actions until the evaluation gate clears on your own reviewed cases. Anything outside its brief goes to a person with the context attached.
Is Meronym an AI development company or an AI consulting company?
Both, with one team. AI consulting defines what to build, what to test and whether the investment is justified. AI development turns that plan into a production system, with the same engineering team staying involved.
How do I choose an AI development company?
Compare five things before choosing an AI development company: published price ranges, who will build the system, proof of production work, how failures are handled and who owns the code at handover. These answers show how the engagement will work before the contract does.
What is an AI development company?
An AI development company designs, builds, integrates and runs AI systems for businesses, including agents, LLM applications, automation and machine learning models. An artificial intelligence development company builds around your workflows, systems and data rather than selling a standard product for you to configure.
Bring Us One Workflow. Get a Clear Plan and Price.
Tell us the workflow, the systems it touches and what success looks like. An engineer replies within two business days with the plan, relevant cost tier and the name of the person who would build it.