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Document understanding
Extract fields, compare versions and summarise long documents with the source passage kept beside every answer.
ServicesGenerative AI development
Generative AI in production
Generative AI Development Company in India
ResoluteX builds generative AI into the software people already use: drafting, summarising, extracting, classifying and answering inside real workflows. Every feature ships with an evaluation set, cost tracking and a fallback, because a demo that works on ten examples is not a product.
A generative AI feature your team can measure, afford at production volume, and switch models under without a rewrite.
Where this work fits
02
Drafting inside workflows
Prepare replies, reports and records for a person to approve, instead of a separate chat window nobody opens.
03
Search and answers
Answer questions from your own knowledge with citations, permission checks and a clear 'I don't know'.
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Classification and routing
Sort tickets, leads, claims or requests at volume, with confidence thresholds that send edge cases to a person.
What you receive
- 01A golden evaluation set built from your real examples
- 02Prompt, retrieval and model configuration in your repository
- 03Per-feature cost tracking and model routing rules
- 04Fallbacks, refusal paths and human review where needed
- 05Evaluation runs in CI, so a model or prompt change is tested before it ships
How delivery works
- 01
Pick one measurable job
We choose a task where a good answer can be judged, and collect real examples of it.
- 02
Score before building
The evaluation set is written first, so every later choice of model, prompt or retrieval is a number, not an opinion.
- 03
Build into the workflow
The feature lands where the work already happens — your app, CRM, helpdesk or internal tool.
- 04
Ship with cost and quality gates
Routing, spend limits and regression evals go live with the feature, and the whole stack is handed over.
A good fit when
- You have a repeated text or document task that people do by hand today
- Someone on your team can judge whether an output is right
- You want to own the prompts, evaluation data and traces
Probably not the right fit when
- The goal is a general chatbot with no defined job or owner
- Outputs must be perfect with no human review and no tolerance for error
- There is no data or example set to learn what good looks like
Questions buyers ask
Before you scope the work
How much does generative AI development cost?
A focused first feature usually fits a fixed sprint between $2.9k and $9.9k over two to four weeks. Model usage is billed by the provider separately and depends on volume and context size, so we estimate it per feature before launch.
Will we be locked into one AI provider?
No. Model routing sits in your code, so moving between OpenAI, Anthropic, Google or open models is a configuration change, tested against the same evaluation set.
How do you measure whether it works?
Against a golden set of real examples with known-good answers. The evaluation runs in CI, so 'the model got worse' becomes a failing check rather than a customer complaint.
Is our data used to train models?
Provider settings, data retention and residency are agreed before the build. We configure providers and keys under your account wherever the engagement allows it.
Related services
Describe the outcome in one sentence. We will return a fixed sprint plan within one business day.
Scope a sprint