Text Generation
Create drafts of reports, emails, product descriptions, and documentation using your terminology and style guidance, with review before publication.
- GPT-4o
- Claude
- Llama 3
- Mistral
Generative AI Development Company
Custom Generative AI Development ServicesFor Enterprises And Startups
We build generative AI solutions that help your team create content, find information, and automate routine work. By combining suitable models with your business data and existing tools, we develop applications designed for daily use, with evaluation and review controls matched to your needs.
Reviewed on Clutch4.9 from 500+ companies
- Capability
- Custom AI Solutions
- Capability
- Workflow Automation
- Capability
- Pilot Development
Models we build on
GPT-4oClaude 3.5 SonnetLlama 3Gemini 1.5 ProMistral LargeStable DiffusionDALL·E 3WhisperMidjourneyMixtral 8x7BGroqDeepSeekGPT-4oClaude 3.5 SonnetLlama 3Gemini 1.5 ProMistral LargeStable DiffusionDALL·E 3WhisperMidjourneyMixtral 8x7BGroqDeepSeek
Put generative AI to work
Give Your Team More Time for High Value Work
Routine writing, growing support queues, and information spread across documents can slow your team down. Our generative AI solutions help create drafts, retrieve relevant knowledge, and shorten repetitive tasks within the tools your people already use.
Reduce Routine Work
Automate drafting, tagging, and summarisation so your team can focus on work that needs judgement.
Support Faster Customer Responses
Generate draft replies using your approved policies and product information, with escalation where needed.
Build AI Features With a Clear Plan
Move from a defined use case to an evaluated application with development and integration support.
Extend Your Existing Systems
Connect AI to your CRM, ERP, and data tools through a phased implementation approach.
What generative AI services do we provide?
What We Build With Generative AI Development Services
End-to-end generative AI services for businesses that want to build, deploy, and scale AI systems: strategy, model development, integration, automation, and post-deployment support.
Generative AI Strategy and Consulting
Identify where generative AI can support your business. We assess readiness, compare potential use cases, and develop a roadmap with estimated costs, dependencies, and success measures.
What you get:
- AI readiness and feasibility assessment
- Prioritised business use cases
- Implementation roadmap
- KPIs and evaluation criteria
Generative AI Integration
Bring generative AI into the systems your team already uses. We plan and implement integrations with your CRM, ERP, SaaS platforms, and internal tools, with attention to access, reliability, and operating costs.
What you get:
- Business system integrations
- Deployment to your agreed cloud environment
- Model monitoring setup
- Performance and cost optimisation
Custom LLM Solutions and Fine-tuning
Adapt language models to your domain, terminology, and output requirements. We evaluate whether prompting, retrieval, or fine-tuning best suits your goals before selecting an approach.
What you get:
- Model selection and solution design
- Domain data preparation
- Fine-tuning where appropriate
- Quality evaluation and benchmarks
Generative AI Application Development
Turn your idea into a usable AI web application. We develop writing assistants, AI search tools, content generation applications, and AI features for SaaS products.
What you get:
- Application design and development
- Web and SaaS integration
- Custom AI product capabilities
- APIs designed for growth and maintenance
AI Copilot and Agent Development
Help your team complete routine work with copilots and agents connected to existing tools. We define permissions, approval points, and exception handling to match the level of autonomy your workflow needs.
What you get:
- Internal AI copilots
- Task-focused AI agents
- Workflow orchestration
- Integration with collaboration and business tools
Retrieval Augmented Generation Development
Make your business knowledge easier to access. We connect language models to approved documents and data sources so users can retrieve relevant information and review supporting references.
What you get:
- RAG architecture and setup
- Document and knowledge base integration
- Context-aware search and Q&A
- Source references and answer-quality evaluation
Generative AI Workflow Automation
Cut repetitive work across customer service, marketing, HR, and operations. We connect generative AI to your existing processes, with review steps for outputs and actions that need human judgement.
What you get:
- Workflow assessment and automation
- Reporting and summarisation
- Customer support assistance
- Integration with business tools
What generative AI systems do we design and deploy?
Generative AI Capabilities for Your Business
Explore the types of AI systems we can combine to support your workflows, with evaluation tailored to each use case.
Image Generation
Generate concepts, marketing visuals, and variations using selected tools and reference assets, subject to brand review and usage requirements.
- Stable Diffusion
- DALL·E 3
- Midjourney
- LoRA
Audio and Speech
Build transcription, speech generation, and audio workflows for customer support, narration, and content production.
- Whisper
- ElevenLabs
- TTS
- Diarisation
Video Generation
Support the creation and editing of marketing videos, training content, and personalised messages. Combine appropriate AI tools with human review for quality and brand consistency.
- Sora-class
- Runway
- Editing
- Dubbing
Code Assistance
Help developers draft code, suggest implementations, refactor existing work, and create tests. Outputs are reviewed against your engineering standards before release.
- Codex-class
- Refactoring
- Tests
- Migration
Multimodal AI
Work across text, images, audio, and video within a connected workflow. Build applications that extract information, answer questions, and summarise supported content formats.
- Vision + Text
- Doc AI
- Search
- Summaries
Find the Right Generative AI Approach
Share the workflow you want to improve. We will assess suitable approaches, discuss estimated running costs, and help you decide whether generative AI fits your needs.
Discuss Your Use CaseWhat have we delivered to businesses?
Real Generative AI Projects. Real Business Results.
A look at what we have built for clients across industries.
LadleAI Kitchen Assistant With RAG Validation
Problem
The existing AI recipe generator produced inaccurate results that missed dietary restrictions and food safety requirements, making it unreliable for real users.
Solution
We built a custom AI kitchen assistant using RAG, GPT-4o, and a dual-layer validation system. Every recipe is checked for dietary compliance, food safety, and cooking accuracy before delivery.
- Recipe accuracy rate
- 90%Recipe accuracy rate
- Faster recipe customisation
- 40XFaster recipe customisation
- Delivery time per recipe
- 30sDelivery time per recipe
FormOléSupport Copilot Grounded In Product Docs
Problem
Support agents answered the same product questions daily by searching four disconnected systems, and first-response time kept slipping past SLA.
Solution
We shipped a support copilot with a cited RAG layer over their documentation, ticket history, and policy base, drafting replies in the agent's own tone with the source attached.
- Tickets auto-drafted
- 68%Tickets auto-drafted
- Faster first response
- 3.4XFaster first response
- Coverage without night shift
- 24/7Coverage without night shift
VoltoxGenerative Reporting For Plant Operations
Problem
Plant supervisors spent the first two hours of every shift assembling handover reports by hand from sensor exports and shift notes.
Solution
We deployed a multimodal generation pipeline that reads machine telemetry, images, and shift notes, then writes the handover report and flags anomalies for a human to sign off.
- Saved per shift
- 2 hrsSaved per shift
- Report accuracy at sign-off
- 97%Report accuracy at sign-off
- Rolled out in one quarter
- 5 sitesRolled out in one quarter
Where does it land inside your business?
Generative AI Use Cases By Business Function
Generative AI rarely transforms a whole company at once. It lands in one function, proves itself, and spreads. These are the six places it lands first.
Marketing And Content
On-brand copy, campaign variants, and creative assets generated in minutes and reviewed by your team, not written from a blank page.
- Campaign and ad copy at scale
- SEO briefs and long-form drafts
- Brand-tuned image generation
Customer Support
Cited answers drafted from your own policies, so agents approve rather than research, and customers stop waiting on a queue.
- Cited reply drafting
- Deflection with grounded chat
- Auto-summarised ticket handover
Sales And Revenue
Research, outreach, and proposal drafts assembled from your CRM and product data instead of a rep's spare thirty minutes.
- Account research summaries
- Personalised outreach at scale
- Proposal and RFP first drafts
Operations
The reporting, tagging, and summarising layer of your operation, handled by a system that never skips a shift.
- Automated shift and status reports
- Document processing pipelines
- Anomaly flagging for review
HR And Enablement
Job descriptions, onboarding material, and an internal assistant that answers policy questions from the actual handbook.
- Role and JD generation
- Onboarding content packs
- Internal policy assistant
Legal And Finance
Contract and invoice review that surfaces the clauses and numbers a human needs to look at, with the source cited every time.
- Contract clause extraction
- Invoice and expense parsing
- Compliance-ready audit trails
Which industries do we serve?
Generative AI Tailored to Your Industry
Every industry has different workflows, data requirements, and expectations for accuracy. We design generative AI around these needs, with appropriate review, access controls, and evaluation for your use case.
- Healthcare
- Finance And Fintech
- Retail And E-Commerce
- Education
- Manufacturing
- Logistics
- Legal
- Real Estate
- Insurance
- Marketing
- Travel
- Media
Your Industry Has Rules.
We Build Around Them.
Regulated data, legacy systems, and low tolerance for wrong answers are normal constraints on our projects, not exceptions. Tell us yours and we will show you what a compliant generative AI system looks like in your environment.
Talk To A Generative AI EngineerWhich technologies do we use to build generative AI?
Put Generative AI To Work With Our Generative AI Tech Stack
We work with the most reliable and widely adopted generative AI technologies available today, and select tools per use case, infrastructure, and performance requirement, never the other way round.
Model choice is a cost decision as much as a quality one. We benchmark on your data first, then pick the smallest model that clears the bar.
01
Large Language Models
- GPT-4o
- Claude 3.5 Sonnet
- Llama 3
- Gemini 1.5 Pro
- Mistral Large
- Mixtral 8x7B
- DeepSeek
02
Image, Audio And Video
- Stable Diffusion
- DALL·E 3
- Midjourney
- Whisper
- ElevenLabs
- Runway
03
Frameworks And Orchestration
- LangChain
- LlamaIndex
- LangGraph
- Haystack
- DSPy
- Semantic Kernel
04
Vector Stores And Retrieval
- Pinecone
- Weaviate
- Qdrant
- pgvector
- Elasticsearch
- FAISS
05
Training And Fine-Tuning
- PyTorch
- Hugging Face
- LoRA / QLoRA
- DeepSpeed
- Ray
- Weights & Biases
06
Cloud, Serving And Guardrails
- AWS Bedrock
- Azure OpenAI
- Vertex AI
- vLLM
- Groq
- Guardrails AI
How do we build and deploy generative AI?
Our Step-By-Step Approach To Generative AI Delivery
Six stages, each with a defined output, so you always know what is being built, why, and what comes next. No stage closes until you have something you can look at.
Contact Us Now- 1
Discovery And Use Case Selection
We map your workflows, data, and constraints, then rank candidate use cases by payback and risk. Output: a scoped use case with success metrics agreed in writing.
- 2
Data Readiness And Architecture
We audit the documents, records, and systems the model will rely on, then design the retrieval, prompting, and serving architecture around them. Output: an architecture your engineers can review.
- 3
Model Selection And Prototyping
We benchmark candidate models on your data (quality, latency, and cost per task) and build a working prototype. Output: a prototype you can put in front of real users.
- 4
Fine-Tuning And Grounding
We fine-tune or ground the chosen model on your corpus, add guardrails, and shape outputs to your tone and format rules. Output: a system that sounds like your business.
- 5
Testing And Validation
We test for accuracy, reliability, and performance under real-world load, including bias checks and user acceptance testing with your team. Output: a quality report and full sign-off before go-live.
- 6
Deployment And Continuous Improvement
We deploy into your environment, monitor quality and cost in production, and keep improving the system for 60 days within the agreed support scope. Output: a system your team owns.
What can your business achieve with generative AI?
Stay Ahead Of The Competition With Generative AI Built For Production
Increased Automation
Generative AI handles repetitive content, data, and communication work so your team can focus on what drives growth. Businesses typically see a 60 to 70% reduction in time spent on manual, repeatable tasks after deployment.
Improved Productivity
AI-assisted workflows speed up decision-making, cut bottlenecks, and give your team faster access to the information they need. Teams report completing projects up to 40% faster than before.
Significant Cost Reduction
Automating tasks and reducing errors can cut operational costs by up to 40%. For most businesses, the ROI on generative AI development becomes visible inside the first six months.
Faster Output Generation
Generative AI produces content, reports, code, and data summaries in a fraction of the time a human team needs. You increase output speed without increasing headcount.
Better Decision Making
Generative systems process large volumes of data and surface clear insights faster than any manual process, so leadership decisions are based on evidence rather than assumption.
Stronger Competitive Position
Companies deploying generative AI today are building a structural advantage over competitors still evaluating it. Faster output, lower costs, and smarter decisions compound into a lead that is difficult to close.
- AI and machine learning projects
- 500+AI and machine learning projects
- Engineers and data scientists
- 85+Engineers and data scientists
- Global markets served
- 30+Global markets served
- Years building production AI
- 4+Years building production AI
Why choose us?
Why Build Generative AI With Axiomra
Work with a team that connects strategy, development, and adoption. We help you define success, integrate the solution, and support your team through launch and the agreed post-deployment period.
Book a Free Consultation01
Clear Project Communication
Follow progress through regular updates, clear milestones, and an identified point of contact.
02
Agreed Success Measures
Track outcomes against measures defined before development, such as turnaround time, output quality, or operating cost.
03
Flexible Ways to Work Together
Choose a fixed scope, a dedicated team, or time-based delivery to suit your project.
04
One Partner Across Delivery
Coordinate strategy, development, integration, and deployment through a single delivery team.
05
60 Days of Post-deployment Support
Address early usage issues and performance adjustments within the agreed support scope.
06
Practical Training and Handover
Give your team the documentation and training needed to use and manage the solution.
Security and Governance Built Into the Project
We agree on data handling, hosting, and access requirements before implementation. Controls are selected for the data and risks involved in your use case.
- Agreed hosting and data access arrangements
- Appropriate handling of personal and sensitive information
- Output controls and human review where needed
- Logging and retention suited to audit and privacy requirements
- Assessment of applicable security and regulatory requirements with your team
Generative AI That Ships.
Not Another Pilot.
Most generative AI projects stall between demo and production. We scope for deployment from the first call and stay on for 60 days after go-live. Start with a free strategy session, no commitment, no generic pitch.
Claim Your Free Strategy SessionGenerative AI, answered
Frequently Asked Questions
Generative AI development services cover everything needed to take a model from idea to production: use case selection, data preparation, model selection or fine-tuning, retrieval and grounding, application development, integration with your systems, and monitoring after launch.
