AI Solutions
Services
Applied AI embedded into business operations — not a generic AI transformation pitch.
Operations and technology leaders who want AI applied to specific, repeatable operational work — not a broad, undefined AI initiative.
Challenges we address
- Teams spending hours reading and re-typing documents
- No way to ask questions about live operations in plain language
- Manual triage of requests, tickets, and applications
- Reports assembled by hand instead of generated automatically
Capabilities
- Operational copilots over live operating data
- Document intelligence — contracts, invoices, inspections
- Automated support for WhatsApp, chat, and voice
- Predictive operations — delays, risk, anomalies
- Intelligent reporting and executive summaries
- Workflow automation — classify, route, escalate
Example use cases
- "Which locations are at risk of missing SLA today?"
- Flagging missing information across inspection documents
- Auto-routing a field incident to the right owner
- Automated daily executive operations brief
Delivery process
- Use-case selection and value assessment
- Data readiness review and guardrail design
- Pilot build with accuracy measurement and human review
- Production rollout, monitoring, and iteration
Business outcomes
- Operational assistance, not unchecked autonomous decisions
- Faster, more consistent document processing
- Decisions supported by evidence, not intuition
- Controlled, auditable AI usage with human review
Technologies
- Python
- LLM platforms
- Document AI
- Vector search
Frequently asked questions
Does this replace staff with automated decision-making?
No — the model is operational assistance with a human review step, not unchecked autonomous decisions. Where a decision has real consequences, a person confirms it.
What data do we need before starting an AI project?
A data-readiness review is the first step of the process — it identifies what's usable today, what needs cleanup, and whether a pilot is realistic before any model work begins.
How is accuracy measured before something goes live?
Every pilot defines an accuracy target and a human-review path for low-confidence cases before rollout, with a measured baseline so improvement is verifiable, not assumed.
Related solutions
Next step
What is slowing your operation down?
Talk to DERA about the workflow, system, or operational bottleneck you need to fix.