AI · Service
LLM Development
Custom applications built on large language models: knowledge assistants, document tools, copilots and automations grounded in your own data, with guardrails, evaluation and monitoring for use across every department.
Working standards on every AI engagement
Secure by default
OWASP-aligned coding, dependency scanning and least-privilege access on every project.
Reviewed code
Every change is peer-reviewed before it is merged and released.
Automated tests
Unit, integration and end-to-end tests run in CI on each commit.
Accessibility
Interfaces checked against WCAG 2.2 AA guidelines.
Performance budgets
Speed targets agreed up front and measured before launch.
Privacy minded
Data collected only when needed and handled with care.
Documented
Architecture notes, runbooks and handover docs you keep.
Transparent reporting
Regular demos, shared boards and plain-language updates.
What we build
LLM Development services
Pick an area to see how we can help, from new builds to long-term care.
Internal knowledge assistants
Staff ask questions in plain language and get answers from policies, manuals and wikis, with sources cited.
Department copilots
Assistants tailored to finance, HR, operations or sales, aware of their documents and tools.
Customer assistants
Website and support assistants grounded in your help content, with hand-off to people.
Document Q&A
Ask questions across contracts, reports and long documents and get precise, referenced answers.
Summaries and drafting
Meeting notes, report drafts and email replies prepared for review.
Extraction
Key fields pulled from unstructured text into your systems.
Text-to-SQL analytics
Plain-language questions turned into safe, read-only queries over your reporting data.
Semantic search
Search that understands meaning across documents, tickets and records.
Classification and routing
Emails, tickets and requests sorted and sent to the right team.
Retrieval pipelines
Ingestion, chunking and vector search tuned to your content.
Guardrails and evaluation
Test sets, quality scoring and safety checks before every release.
Hosting choices
Hosted APIs, private cloud or self-hosted open models, chosen for privacy and cost.
01
Grounded in your content
Retrieval-augmented generation keeps answers tied to your own documents and records, so the model explains what your business actually says rather than guessing.
- Ingestion from drives, wikis and systems
- Answers with citations
- Permission-aware access
02
Measured before it ships
We build evaluation sets from real questions, score accuracy and tone, and only release when results meet the bar you agreed.
- Task-specific test sets
- Automated quality scoring
- Regression checks on every change
03
Where your people already work
Assistants are available in Slack, Microsoft Teams, your intranet, helpdesk or CRM, so adoption does not depend on another login.
- Chat tool integrations
- Embedded widgets
- Single sign-on
04
Private, controlled and observable
Data handling, model choice and hosting are designed around your privacy needs, and usage, cost and quality are monitored in production.
- No training on your data
- Usage and cost dashboards
- Audit logs
Engagement models
Work with us your way
Fixed Scope
A defined scope, timeline and price for projects with clear requirements.
- Agreed deliverables
- Milestone-based billing
- Change requests handled openly
Dedicated Team
A team that works only on your product, sized to your roadmap.
- Developers, QA and a lead
- Monthly capacity you can adjust
- Works in your tools and rituals
Time & Materials
Flexible, pay-as-you-go engagement for evolving or exploratory work.
- Billed on hours used
- Reprioritise any sprint
- Weekly time reports
Expertise
LLM expertise for real workloads
We focus on dependable LLM applications: clear scope, good retrieval, honest evaluation and integrations that make them useful day to day.
Talk to an expert →Retrieval
- Document ingestion
- Vector search
- Hybrid ranking
- Citation handling
Applications
- Knowledge assistants
- Copilots
- Document Q&A
- Text-to-SQL
Quality
- Evaluation sets
- Guardrails
- Human feedback loops
- Prompt and tool design
Operations
- Hosted or self-hosted models
- Access control
- Monitoring
- Cost management
How we work
A clear path from idea to launch
- 01
Discovery
Workshops to understand goals, users, systems and constraints.
- 02
Plan & Estimate
Scope, architecture and a phased roadmap with estimates.
- 03
Design
User flows, wireframes and visual design, validated with you.
- 04
Build
Short sprints with demos, code review and automated tests.
- 05
Test & Launch
QA, performance checks and a rehearsed go-live.
- 06
Support & Grow
Monitoring, fixes and a continuous improvement backlog.
Technology
The stack behind AI
LLM APIs
Hosted language models with guardrails
Open models
Self-hosted where data must stay in-house
Python
Data and ML services
Evaluation sets
Measured quality before release
Vector search
Retrieval over your documents
PostgreSQL
Structured business data
OCR
Scanned forms, invoices and receipts
Text-to-SQL
Plain-language questions over reports
REST APIs
Connect ERP, CRM and helpdesk
Queues
Reliable background automations
Slack & Teams
Assistants where people already work
Inbox triage and drafting
Access control
Answers respect who is asking
Audit logs
Every action traceable
Monitoring
Quality, cost and latency tracked
Cloud & on-prem
Deployed where your data lives
No matching technologies.
Why AI
AI that makes every team more productive.
The biggest gains rarely come from a chatbot on the homepage. They come from the hours your teams spend searching, copying, summarising and re-keying, every day.
Hours back every week
Routine replies, data entry and report preparation handled automatically, with people reviewing what matters.
Answers from your own knowledge
Policies, contracts, manuals and tickets become searchable in plain language, with sources cited.
Fits existing systems
Assistants read from and write to your ERP, CRM, helpdesk and shared drives, not a separate silo.
Safe by design
Permissions, human approval steps, audit logs and data that stays where you choose.
103+
Projects delivered
52+
Platforms supported
9+
Years in commerce
We choose hosted or open models for each use case based on quality, cost and privacy needs, and can switch later without rebuilding the application.
No. We use providers and settings that do not train on your data, or deploy models in your environment.
With retrieval from trusted sources, citations, evaluation sets, guardrails and human review for sensitive tasks.
Yes. Retrieval follows your existing permissions, so people only get answers from content they can access.
A focused pilot over one knowledge source or workflow often takes a few weeks. We agree scope and success measures before starting.
Start a project
Let’s talk about your AI plans
Tell us what you are working on. We reply within one business day with next steps and, where it helps, a short call.