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AI & Automation
AI Solutions & Automation
We build AI into products where it removes real work — document processing, support deflection, search over internal knowledge, drafting and classification. Every engagement starts with the cost of the current manual process.
Practical AI features and workflow automation aimed at measurable time and cost savings.
Get a QuoteThe problem
AI pilots that never reach production
Demos are easy. Production is where things break: no evaluation set, no cost ceiling, no handling of wrong answers, no access control over the data the model can see. We build for that second part from the start.
Sound familiar?
- A promising prototype that nobody trusts with real customers
- Model costs that are impossible to forecast
- Answers that cannot be traced back to a source
- Staff still doing the manual step the pilot was meant to remove
What we deliver
Exactly what you receive.
Every engagement has defined outputs. Nothing on this list is an optional extra quoted later.
- Use-case assessment with a cost and feasibility ranking
- Data readiness review and access model
- Prototype on your real data, not a sample
- Evaluation set and accuracy benchmark
- Production integration inside your existing product
- Guardrails, fallbacks and human review paths
- Cost monitoring and usage limits
- Handover with a plan for ongoing evaluation
Capabilities
What this service covers.
AI assistants
Support and internal assistants grounded in your documentation, with citations and a clear escalation path.
Document processing
Extraction and classification for invoices, contracts and forms, with confidence scores and review queues.
Semantic search
Search across internal knowledge that respects existing permissions and returns the source, not just an answer.
Workflow automation
Triggered pipelines that move data between systems, with retries, logging and alerting when something fails.
AI product features
Drafting, summarisation, tagging and recommendations built into the product your users already use.
Business intelligence
Reporting pipelines and dashboards that turn operational data into a number a manager can act on.
Technologies
The stack we use for this work.
- OpenAI API
- Claude API
- Vector databases
- Python
- Node.js
- TypeScript
- PostgreSQL
- AWS
Tool choices are made per project, against your team’s existing skills and what you already run in production.
Process
- 01DiscoverUnderstand the business, the users and the constraint that matters.
- 02StrategizeDefine scope, architecture and the order things get built in.
- 03DesignFlows, interfaces and a system developers can build without guessing.
- 04BuildTwo-week increments against a staging environment you can open.
- 05TestQA across devices, load, security and the paths that matter most.
- 06LaunchA rehearsed release with monitoring in place before traffic arrives.
- 07GrowSupport, measurement and the next round of improvements.
Benefits
What changes for the business.
- 01
Measured against the manual cost
We baseline the hours a process takes today, so the value of automating it is a number rather than a feeling.
- 02
Wrong answers handled by design
Confidence thresholds, citations and human review keep an imperfect model safe to put in front of customers.
- 03
Predictable spend
Caching, model routing and hard usage limits keep costs inside a budget you set before launch.
Related work
Where we have done this before.
FAQ
Questions we are asked about ai & automation.
Not without your explicit decision. We default to providers and configurations where submitted data is excluded from training, and we document exactly what leaves your infrastructure.
Let’s build
Ready to talk about ai & automation?
Send us the brief, the problem, or just the deadline you are working towards. We will come back with an approach and a realistic estimate.
Prefer email? info@saftasoft.site