Recommendation AI Software

Show every rep, agent and customer the recommended next move — product, content, offer or action — ranked from their own record.

Next best action

on every record

Cross-sell

& upsell signals

Content

matched to stage

Real-time

recommendations

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AI Intelligence Layer

Overview

Recommendation AI answers the question every team faces: what next? The Flow-Cognition Agent reads each customer's history, behaviour and stage, then recommends the next best action for your team or the most relevant product, content or offer for the customer — all grounded in your own data.

Recommendations appear in the flow of work, on the record and in the conversation, so no one has to go looking. Each one is explainable and governed, and where you allow it, the agent can act on the recommendation directly instead of leaving it as advice.

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✓ Next-best-action guidance for sales, support and success teams
✓ Product recommendations tuned to each customer's history
✓ Content and offer recommendations matched to intent and stage
✓ Grounded in your own catalogue, records and behaviour
✓ Delivered in the flow of work, right on the record
✓ Explainable and governed, with optional act-on-recommendation

Capabilities

Everything Recommendation AI gives you

Six ways Recommendation AI turns data into the next best action — every time.

Next Best Action

AI recommends the optimal next step for every deal, ticket and campaign — call, email, offer, escalate or wait.

✓ Context-aware
✓ Timing optimization
✓ Channel recommendation
✓ Action priority

Cross-Sell & Upsell

Identify expansion opportunities using product usage, engagement patterns and purchase history to recommend the right offer.

✓ Product affinity
✓ Timing signals
✓ Offer matching
✓ Revenue potential

Content Recommendations

Suggest the best content — case studies, demos, docs — for each prospect based on industry, stage and engagement.

✓ Stage-aware
✓ Industry matching
✓ Engagement-based
✓ Personalized

Response Recommendations

Suggest optimal support responses based on issue type, customer history, sentiment and resolution patterns.

✓ Issue matching
✓ History-aware
✓ Sentiment-adjusted
✓ Resolution optimization

Strategy Recommendations

Highlights patterns across accounts, such as which products sell together or which segments respond to which offers, for managers to act on.

✓ Portfolio analysis
✓ Market insights
✓ Resource optimization
✓ Strategic guidance

Recommendation Analytics

Track recommendation acceptance rates, impact on outcomes and model accuracy with full transparency.

✓ Acceptance tracking
✓ Outcome impact
✓ A/B testing
✓ Model transparency

AI at work

How the agent works with Recommendation AI

The Flow-Cognition Agent runs a real loop on your Recommendation AI data — grounded in your records, governed and logged.

Sense

Reads purchase history, engagement, stage and open tickets.

Decide

Ranks actions, products and content by likely value for this customer.

Act

Shows the recommendation on the record or in the conversation, or carries it out where permitted, and logs the outcome.

Five-tier model routing · field-level permissions · full audit trail. See the AI layer →

How it works

Live in four steps

Read the record

The agent gathers the customer's history, behaviour and current stage.

Rank the options

Actions, products, content and offers are scored for this customer.

Surface in context

The best recommendation appears on the record and in the conversation.

Act or advise

The team acts, or the agent executes it directly where allowed.

Use cases

Where teams put it to work

Sales reps

On every open deal the rep sees the next best action, whether to send a case study, propose an upsell or schedule a call, ranked for that specific account.

Support and success

Agents get recommended help articles and save offers tuned to the customer's issue and history, resolving faster and reducing churn.

E-commerce and retail

Shoppers see product and offer recommendations based on their own browsing and purchase history, lifting basket size and repeat sales.

Why it matters

The payoff

Less guesswork

Each record shows a ranked next move and the signals behind it.

Relevant to each person

Recommendations reflect the individual's own data, not a broad average.

More upsell and retention

Timely, fitting offers and actions lift conversion and loyalty.

Advice that can act

Where allowed, recommendations become executed actions, not just tips.

FAQ

Questions, answered

It is the single most valuable move to make on a given record right now, chosen by the AI from all the options and ranked for that specific customer and context.

They are grounded in your own catalogue, records and behavioural history, so product, content and offer suggestions reflect what actually fits each customer.

They surface in the flow of work, directly on the record and in the conversation, so teams see them without switching tools or going looking.

Yes. Where you permit it, the Flow-Cognition Agent can execute the recommended action directly, within guardrails and permissions, instead of leaving it as advice.

Yes. Each recommendation is explainable, showing the signals behind it, so teams can trust the suggestion and apply their own judgement.