Services
AI Integration & Automation
AI integration is the work of connecting large language models and machine-learning tools to a company's actual systems and workflows so they automate real tasks — answering customer questions, extracting data from documents, drafting reports. Sors Technology builds AI automations on OpenAI, Anthropic Claude and Google Gemini models, integrated with your ERP, CRM and communication channels.
Who this is for
- Businesses where skilled staff spend hours on repetitive text and data work — retyping documents, answering the same questions, assembling reports
- Companies with an ERP or CRM in place that want more value out of the data already flowing through it
- Teams that tried a chatbot or an AI pilot that impressed in a demo and then quietly died
Who this is not for
- Organisations looking for AI to replace decisions that carry legal or safety consequences — we automate the work around judgment, not the judgment
- Businesses without digitised processes yet; if operations live on paper, start with ERP or custom software first, and we will say so
Problems we solve
| Where you are | Where we get you |
|---|---|
| Staff retype supplier invoices, orders and forms into your systems | Document extraction that reads PDFs, images and emails and posts structured data for human approval |
| Customers wait hours for answers your website already contains | An assistant grounded in your real documentation that answers instantly and hands off to humans gracefully |
| Weekly reports consume a day of copy-paste across systems | Generated first drafts from live data — humans review, not assemble |
| Support tickets, reviews and emails pile up unread | Automatic triage, tagging and routing with sentiment and urgency detection |
| Every extra language multiplies your content budget | AI-assisted translation and adaptation pipelines with human editorial control |
What's included
Automation audit
We inventory your repetitive work and score each candidate by volume, error cost and feasibility — you get a ranked list, including what not to automate and why.
Model and platform selection
The right model for each job — OpenAI, Claude, Gemini or open-weight models — balancing quality, cost per task and data-handling requirements.
Integration engineering
The unglamorous part that makes it real: connections to your ERP, CRM, inboxes and file stores, with queues, retries and logging.
Retrieval over your knowledge
RAG pipelines that ground model answers in your actual documents, prices and policies — so the assistant cites your truth, not its imagination.
Human-in-the-loop controls
Approval steps, confidence thresholds and full audit logs. Automation proposes; accountable people dispose.
Measurement
Per-automation dashboards: tasks handled, hours saved, error rates, cost per run — so ROI is a number, not a feeling.
Our approach
- 01
Audit
One to two weeks shadowing real work. Output: a ranked automation backlog with effort and payback estimates.
- 02
Prove
One narrow, high-volume workflow built end to end in weeks — measured against the manual baseline.
- 03
Harden
Error handling, approval flows, monitoring and cost controls before anything touches production data unattended.
- 04
Extend
Roll the pattern across the backlog, one workflow at a time, keeping each one measured.
Platforms and technologies
Anthropic Claude
Long-document analysis and reliable structured output
OpenAI GPT
Broad capability and ecosystem
Google Gemini
Multimodal tasks and Workspace integration
Open-weight models
Llama-class models where data must stay on your infrastructure
n8n / Make
Workflow orchestration without lock-in
pgvector / Elasticsearch
Retrieval over your documents
Related industries
Outcomes we target
- Hours of repetitive work removed per person per week — measured, not estimated
- Response times cut from hours to seconds on covered topics
- Document processing error rates below manual baselines
- A reusable integration layer that makes the next automation cheaper
- A team that understands what AI can and cannot do for the business
Frequently asked questions
Reliably today: extracting data from documents, drafting and answering routine correspondence, triaging tickets, summarising and translating content, and assembling first-draft reports from live data. The pattern: high-volume text and data tasks with clear success criteria and human review where it matters.
It cannot fix undocumented processes, decide strategy, or take responsibility. It makes errors confidently, which is why we build approval steps and measurement into every workflow. Anyone promising a fully autonomous business is selling something.
We use commercial API tiers where prompts are not used for model training, and open-weight models on your own infrastructure where residency or confidentiality demands it. Data handling is documented per workflow, and EU-facing clients get EU-compliant configurations.
Most document and correspondence automations cost cents per task in model fees. The real investment is the integration engineering around them; that is a one-time cost the audit quantifies before you commit.
No. We hand over dashboards, plain-language runbooks and alerting. Where a workflow needs prompt or rule adjustments, we train a named person on your side — or cover it under support.
Related services
ERP Implementation
One system for finance, inventory, sales and operations — replacing the spreadsheets your business has outgrown.
CRM Implementation
A sales pipeline the whole company can see — so revenue stops depending on individual memory.
Custom Software & Web Applications
Purpose-built platforms and portals for the process that makes your business different.
Tell us what is slowing your business down
Send us your goals and current setup. Within 48 hours you get a written assessment with a recommended approach, a realistic timeline and an honest budget range.