AI & Automation

Your partner in AI solutions & LLM

Retrieval pipelines, fine tuned models and tool using agents that hold up under production load. We measure accuracy before you commit budget.

Generative AI and ML solutions we deliver

Generative AI Strategy

We define use cases tied to KPI, audit your data, constraints, and risks. Prioritized backlog for Generative AI, LLM, and predictive initiatives with clear acceptance criteria.

Model Selection & Architecture

We compare LLMs (managed APIs vs open source) and ML frameworks. We choose the right toolchain for your domain based on cost, latency, privacy, and grounding requirements.

Prototype deployment

We ship a thin path (API or lightweight UI) to validate quality, hallucinations, throughput, and operations. RAG, prompt flows, and guardrails connected to your systems. Pilot metrics + best recommendations for production.

Optimization & Scaling

We tune cost/quality, add eval sets and monitoring, set safety filters and retraining loops. We provide a production plan that scales your GenAI solution with Oligamy Software as your delivery partner.

How we ship machine learning to production

Data Discovery & Feasibility

We analyze your raw datasets for quality, completeness, and predictive power. We define target variables (what to predict) and establish baseline metrics.

You get: Data audit report, feasibility study, and defined success metrics (RMSE, Accuracy, F1-score).

Feature Engineering & Modeling

We clean data, select relevant features, and experiment with various algorithms (Regression, XGBoost, Neural Networks) to find the best fit. We balance complexity with interpretability.

You get: Trained candidate models, feature importance analysis, and initial validation results.

Validation & Stress Testing

We test the model against unseen data (hold out sets) to prevent overfitting and ensure generalization. We simulate edge cases and assess performance under load.

You get: Model performance report, error analysis, and ready to deploy model artifacts.

Deployment & MLOps

We containerize the model, set up inference pipelines (batch or real time), and implement drift detection to monitor model degradation over time.

You get: Production API, monitoring dashboard (Data Drift), and automated retraining pipelines.

What we measured

Numbers from two production systems we built, not industry averages. Each one links to the engineering note that documents how it was measured.

98.2%: First-pass classification accuracyCustom LLM fine-tuned on roughly 2,000 labeled domain examples. The ambiguous 1.8% is flagged for human review rather than guessed.Document classification, engineering note
96 to 99%: Retrieval accuracy in productionRetrieval augmented generation across more than 50,000 documents in regulated industries.RAG at scale, engineering note
96%: Lower cost per queryRetrieving only relevant passages instead of pushing long context into every call.RAG at scale, engineering note
340 h: Manual review removed monthlyHours the same client previously spent reading documents by hand every month.RAG at scale, engineering note

Errors per 100 documents, before and afterSame corpus, same reviewers. Lower is better, so the bars show mistakes rather than accuracy: at 96 and 99 percent the difference is one bar length, in errors it is four times fewer.

Before, keyword search and manual triage4 errors

After, retrieval augmented generation1 error

Derived from the 96 to 99 percent accuracy figure in the RAG engineering note. A fourfold drop in errors is what changes whether a person has to check every output or only the flagged ones.

AI & LLM solutions included by Oligamy Software

Process automation

LLM agents and workflows that reduce manual effort, errors, and lead times.

Customer experience

Personalization, recommendations, and dynamic content powered by AI solutions & LLM.

Analytics & decisioning

Pipelines, feature stores, and LLM assistants that surface trends and speed up decisions.

Automation & workflow support

Add reasoning and context automation to your software - ticket triage, document parsing, or content moderation.

AI infrastructure setup

Implement monitoring, evaluation, prompt management, and retraining pipelines to make LLM stable and measurable in production.

Custom solution for LLM project

Every project is different - we design and ship tailored AI & LLM implementations that fit your stack and users, using trusted technologies, not proprietary products.