We build forecasting, search, and language tools with real pipelines, clear baselines, and deployable APIs.
Practical data systems that move from raw records to decisions people can defend
Define the events, KPIs, and collection paths that make decisions measurable instead of anecdotal. We help teams capture the right data before modeling begins.
Design reliable data stores that consolidate operational sources, preserve definitions, and give reporting and model pipelines a clean source of truth.
Build models for demand, revenue, risk, and capacity planning, with holdout tests and baseline comparisons that make performance interpretable.
Separate signal from noise with experiments, causal reasoning, uncertainty estimates, and decision thresholds that match the business risk.
Turn recurring questions into dashboards, alerts, and workflows that help operators compare, diagnose, and act without waiting on ad hoc analysis.
Choose the right level of automation, model complexity, and deployment architecture for the job, from classical models to local language systems.
Working applications on real public datasets — open one and inspect the behavior yourself
Daily revenue forecasts for a UK online wholesaler, backtested on weeks the model never saw and scored against naive baselines.
Search 20,000 real job postings across three ranking algorithms, with faceted filters, skills extraction, and market analytics.
Speak or type, and two open models running on our infrastructure do the rest: Whisper transcribes speech, then TranslateGemma translates it. Optional browser read-aloud is disclosed inside the demo.
Each public demo stands for a reusable business pattern, not a toy dataset.
What it proves: historical transaction data can become an auditable planning system with measured error.
Business analogue: demand planning, cash forecasting, inventory risk, staffing, and capacity decisions.
What it proves: messy text records can be ranked, filtered, and explained in an operator-facing workflow.
Business analogue: internal knowledge search, candidate matching, procurement search, support triage, and document discovery.
What it proves: open models can run behind your API with visible latency, quality limits, and deployment constraints.
Business analogue: multilingual support, internal translation, voice intake, and regulated workflows where routing data matters.
RightInference is a practical data consulting practice for teams that need working systems, not slideware. We turn messy operational data into models, dashboards, and APIs that can be tested against real outcomes.
The live apps above are part of the pitch: they show how we think about evidence, latency, baselines, deployment constraints, and user-facing workflows before your own data enters the room.
Models are compared against baselines and reported with the limits visible
Work is shaped around APIs, queues, reliability, and the environment it will run in
Technical choices are tied back to decisions, costs, and operational tradeoffs
Ready to make better decisions with your data? Let's talk.
contact@rightinference.com
Monday - Friday: 9:00 AM - 6:00 PM