ia.
internal automation

Internal Automation
Built to work. Yours to run.

AI Reward Signals & RLHF. Positive reinforcement.

Reward functions that teach your AI what good looks like. Design reward functions and human feedback pipelines that align your AI systems with your business values and customer expectations.

Book a Fusion Workshop
Yoursyou define the objective, the reward, the constraints
LoRAopen-weight policies, fast iteration, weights owned by you
Sim-firstthousands of scenarios run before production
10-80-10payment terms: start, build, handover

The spec.

The build, stage by stage. This is what the design phase papers and prices.

01TriggerModel outputs. Candidate responses to evaluate.
02The readScore + rank (RLHF). Outputs are judged for quality and preference.
03The writeTraining pipeline. Signals feed your fine-tuning runs.
04The handoffReward signal. A reliable gradient toward the behavior you want.

You own the build. The workflow, the integrations, and the credentials live in your accounts, not ours. Documented, handed over, yours.

Fixed price. Fixed date.

01FusionA Fusion Workshop. Your team and ours, one room, the workflow on the whiteboard. You leave with the plan whether or not you hire us.
02DesignWe spec the build: every trigger, every integration, every handoff. It ends with a fixed price and a live date.
03BuildThe first workflow is live in weeks; a full deployment runs three months to a year. 10% to start, 80% across the build, 10% at handover.
04RunIt runs in your accounts under your credentials. Keep us on support, or take the keys.

The walk-away: If automation will not pay for itself in your operation, we say so at the workshop, and you keep the map.

What we need from you: a decision-maker in the workshop, system access by week one, and honest answers about how the work really flows.

Adjacent builds.

Most engagements expand into one of these after the first build proves out.

Computer Vision and Vision ModelsAI-Powered iOS and Mobile AppsAI Data Annotation and LabelingAI Chatbots and Virtual AssistantsWorkflow Automation

Straight answers.

What is RLHF and why does my business need it?

RLHF stands for Reinforcement Learning from Human Feedback. It is a technique where human evaluators rate AI outputs, and those ratings are used to train the AI to produce better responses over time. Your business needs it whenever you deploy AI that interacts with customers or makes decisions that affect your brand. Without RLHF, AI systems optimize for generic metrics that may not align with your specific values, tone, or business priorities. With RLHF, your AI learns to behave exactly the way your best employees would.

How much human feedback is needed to align an AI system?

The amount varies by complexity, but most business applications achieve strong alignment with 500 to 2,000 rated examples. We design efficient feedback collection workflows that integrate into your team's existing processes, for example, having customer service staff rate chatbot responses during quiet periods, or having managers review AI-generated recommendations weekly. The process is ongoing but becomes lighter over time as the AI internalizes your preferences and generates fewer outputs that need correction.

Can RLHF fix an AI that is already giving bad outputs?

Yes, RLHF is one of the most effective techniques for correcting AI behavior. If your current AI is too aggressive in sales pitches, too formal or too casual in tone, missing important nuances, or generating occasionally inappropriate content, RLHF can systematically correct these issues. We start by identifying the specific behavior patterns that need adjustment, collect targeted feedback on those patterns, and retrain the model. Most behavioral issues can be significantly improved within 2-4 weeks of focused RLHF training.

How do you measure whether AI alignment is working?

We establish quantitative alignment metrics at the start of every engagement. These typically include human evaluation scores on key dimensions like helpfulness, accuracy, tone, and safety, plus automated metrics like customer satisfaction ratings, escalation rates, and complaint frequency. We track these metrics over time to demonstrate improvement and identify areas that need further tuning. Monthly alignment reports show exactly how your AI's behavior is trending relative to your defined standards.

Put it to work. Book a Fusion Workshop. →