Data engineering & analytics
Pipelines and a warehouse that make your numbers consistent enough that two teams stop arriving with different answers.
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Data & AI
AI & intelligent automation
Apply language models and automation to the specific processes where they pay for themselves — and skip the ones where they do not.
- Discovery, then build
- From USD 16,000
- Updated
The short answer
AI and intelligent automation apply language models and workflow automation to business processes. LDelight identifies where the economics genuinely work, builds the integration with evaluation and human review, and is candid about the cases where conventional software is the better answer.
Key takeaways
- Business case first — many AI proposals do not survive one
- Retrieval grounded in your own data, with citations
- Evaluation harness so quality is measured, not asserted
- Human review on anything consequential
The useful applications of language models in a business are narrower and less glamorous than the marketing suggests: document understanding, support triage, internal search over scattered knowledge, and drafting where a human always reviews.
We start with the economics
Volume, current cost per transaction, acceptable error rate. If the numbers do not work — and often they do not — we say so before anyone has spent a budget. Deterministic software remains the right answer for a great many problems.
Grounding and evaluation
Where we do build, retrieval is grounded in your own documents with citations back to the source, and an evaluation set is built before the feature ships so quality changes are measurable rather than anecdotal.
Humans in the loop
Anything that touches a customer commitment, a payment or a legal position goes through review. Confidence thresholds route the uncertain cases to a person rather than guessing.
What you get out of it
-
Automation applied where it demonstrably pays
-
Outputs traceable to a source document
-
Quality measured against a fixed evaluation set
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A candid answer on the ideas that do not work
Talk to an engineer about AI & intelligent automation
A 30-minute scoping call. No slide deck, no obligation — you leave with a written recommendation.
What's included
- Use-case assessment with a business case per candidate
- Data readiness review
- Prototype with an evaluation harness
- Retrieval and grounding implementation
- Integration into existing workflows
- Human-review and escalation design
- Monitoring, cost controls and guardrails
- Team training and handover
Technology we use
- Claude API
- OpenAI API
- Azure OpenAI
- AWS Bedrock
- pgvector
- Pinecone
- LangChain
- Python
- TypeScript
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