FeatureStream turns your private business context and market signals into a dynamic product roadmap. Built for product managers, product owners and product creators within AI agent companies.
Context-aware product management for teams building AI agents.
Product owners of AI agents manage customer, market, domain, use case and product usage signals across too many tools to know what to build next. Customer needs shift, agent behaviour changes, competitors ship. FeatureStream keeps all of it in view and tells you what to build next.
Built to streamline the process involved in creating and managing an agentic product.
Signal ingestion
Private and external signals, synthesised.
Evidence, not instinct
Every suggestion comes with the proof behind it. Approve or reject with confidence.
Built for agents
New features. Agentic fixes. Use case expansions. Agentic UI design. Made for how agents actually ship.
Sharper each launch
Ship it. Measure it. The result feeds your next recommendation.
Built around your workflow
Connects to the tools you already use.
FeatureStream integrates with the tools your team already uses, reads from them directly and synthesises signals to create a ranked list of suggestions by impact your product owner can approve or reject.
Observability platforms
Datadog, New Relic, Grafana
CRM & Note-taking
Salesforce, HubSpot, Notion
Customer support & ticketing
Intercom, Zendesk, Linear
Usage analytics
Mixpanel, Amplitude, PostHog
Built for agentic products
Track what matters in your agentic product. From every request to every outcome.
FeatureStream surfaces the most impactful features for your AI agent, refreshed continuously from your live signals. Approve or reject each one, then ship straight to Jira.
Customer signals ranked by evidence
Competitor gaps surfaced by use case
Approved features shipped straight to Jira
Product Feature Selection
Ship to Jira
Ship to Product Catalogue
DomainCustomer support▾
CompanyNorthwind AI▾
All (12)
New feature (4)
Use case expansion (2)
Agentic UI design (2)
Agentic fix (4)
Competitors (5)
New featureLet the agent refund small orders on its own
Why: 6 lost deals blamed slow refund approvals. 4 of 5 competitors automate small refunds.
6 lost deals4 of 5 competitors
91
Approve
Approved
Reject
Learn more
Agentic fixStop the agent hallucinating refund policies
Why: Eval score fell 94 to 81 after prompt v14, and 7 traces show invented terms.
Eval 94 to 817 traces
84
Approve
Reject
Learn more
Use case expansionWarn customers about late orders before they ask
Why: The agent only replies when asked. 5 customers want proactive delay alerts.
5 customers4 of 5 competitors
76
Approve
Reject
Rejected
Learn more
Agentic UI designFlag shaky answers so a person can check them
Why: Teams re-read every AI reply. Flagging unsure ones lets them check only those.
4 customers
See wireframe
71
Approve
Reject
Learn more
New featureLet the agent refund small orders on its own91×
REASONING
Refund approvals are the slowest step in support, so customers wait days and some leave. Six lost deals this quarter named refund speed, and four of the five competitors we track already let their agent approve small refunds.
WHO ASKED+ 5 more requests · 6 lost deals
“Can the agent refund small orders itself? Waiting costs us customers.”
Northwind customer · 2d ago
“We nearly cancelled because a $20 refund took three days.”
Northwind customer · 5d ago
BUILD TIME
3 weeks
one engineer
RISK
Medium
wrong refunds above limit
REVENUE
+$140K
kept from lost deals
TIME TO REFUND
−2 days
now minutes
HOW CUSTOMER USAGE IMPROVES
Refunds finished in chat
22% → 80%
Chats solved without a person
58% → 71%
Customers who come back
41% → 52%
Align your team around what to build next.
Approved features drop straight into your roadmap, sorted into Now, Next and Later based on real customer insights and usage analytics — tying everything back to what you should build, when, and why.
Product Roadmap
Ship to Jira
Ship to Product Catalogue
Customer support · Northwind AI
Roadmap
Roadmap
Timeline
Timeline
Archive
SHOWProduct featuresUse case expansionsAgentic UI designAgentic fixesAuto-add approved
NOW1+
NEXT1+
LATER01+
Let the agent refund small orders on its own
88
New feature
Stop the agent inventing refund policies
48
Agentic fix
Warn customers about late orders before they ask
47
Use case expansion
+Add⌄
Added Warn customers about late orders before they ask to Later.
Add to the roadmap
Click a name to place it by rank, or pick a column.
Warn customers about late orders before they ask
NowNextLater
Reply in the customer's language
NowNextLater
Hand the full chat to a person
NowNextLater
Finish returns reliably
NowNextLater
Show order progress inside the chat
NowNextLater
✳Use cases
Today
2026 Q4
2027 Q1
2027 Q2
REFUNDS
Resolve refunds without waiting on a person
Let the agent refund small orders on its own
9 signals
STATUS
Customers always know where their order is
Warn customers about late orders before they ask
5 signals
HANDOFF
Right answers, and a person when it matters
Stop the agent inventing refund policies
7 signals
Built one after another in roadmap order: Now, then Next, then Later. Open a bar for its dates.
Know exactly what you've built.
Keep track of every product detail with the Product Catalogue.
Customer requests organised by product features, errors and UI changes.
The reasoning behind each recommended feature and use case.
Features tagged by status: Planned, In Development, Shipped.
Prompt and version changelogs for agentic errors.
Overview
Customer requests
Feature status
Impact
Changelog
Documents
Post-launch evaluation
Historical features
Ask AI Assistant
Product Catalogue
Source of truth
Generate document
Customer support
Northwind AI
Search features
FEATURES
4
IN ROADMAP
3
SHIPPED
1
DROPPED
0
BY TYPE
New feature 2Agentic fix 1Use case expansion 1
Feature and why build
Status
Column
Evidence
Impact
Let the agent change a delivery address
New featureShipped Aug 3 · built in 4 weeks
Shipped
Live
7 signals
$45K won back · CSAT 4.1/5
Let the agent refund small orders on its own
New feature6 lost deals, 4 rivals ship it
In development
Now
9 signals
$140K in lost deals
Stop the agent inventing refund policies
Agentic fix7 signals of invented policies
Planned
Next
7 signals
Eval 81 back to 94
Warn customers about late orders before they ask
Use case expansion5 requests · starts Nov 16
Planned
Later
5 signals
$18K in lost deals
Product features
14
Product errors
7
UI changes
0
We nearly cancelled because a $20 refund took three days.
Sep 28 · $30K deal
⚭ Let the agent refund small orders…
Our team spends hours approving $15 refunds by hand.
Sep 27 · $20K deal
⚭ Let the agent refund small orders…
Customer said refunds are the one thing that must be automatic.
Sep 26 · $18K deal
⚭ Let the agent refund small orders…
Refunds took a week last time, so we switched vendors.
Sep 24 · $25K deal
⚭ Let the agent refund small orders…
The agent should just handle small refunds without a ticket.
Sep 20 · $22K deal
⚭ Let the agent refund small orders…
Agent offered store credit plus cash back. Policy allows one or the other.
Sep 22
⚭ Stop the agent inventing refund…
Agent claimed gift cards are refundable. They are not.
Sep 12
⚭ Stop the agent inventing refund…
Agent promised a full refund on a final-sale item.
Sep 10
⚭ Stop the agent inventing refund…
Show all 14
Show all 7
No approved features of this kind.
Planned
2
In development
1
Shipped
1
Stop the agent inventing refund policies
Agentic fix
7 requests · est. 2 weeks · starts Nov 2
Target: Back to Eval 94, then hold it
Warn customers about late orders before they ask
Use case expansion
5 requests · est. 4 weeks · starts Nov 16
Target: Fewer 'where is my order' chats
Let the agent refund small orders on its own
New feature
9 requests · due Nov 2
Week 1 of 3
Target: Eval 90+ on refund tests, 2 weeks after launch
Let the agent change a delivery address
New featurePartly met
Shipped Aug 3 · built in 4 weeks (est. 3)
$45K won back · 43% usage · CSAT 4.1/5
Predicted vs actual
$140K
Let the agent refund small orders on its own
Revenue in 6 lost deals that cite this gap.
Deal · Sep 28
$30K
Deal · Sep 24
$25K
Deal · Sep 7
$25K
+2 smaller
$18K
Warn customers about late orders before they ask
Revenue in 1 lost deal that cites this gap.
Deal · Sep 8
$18K
+13eval pts
Stop the agent inventing refund policies
Eval score to win back, from 7 signals.
Before
94
Now
81
ESTIMATE
$158K
in lost deals behind 2 approved features, lost Sep 1 – Sep 28.
+13
eval points to win back across 1 fix.
Lost-deal revenue by week
Deals lost, linked to approved features
$47K
Week of Sep 1
$18K
Week of Sep 8
–
Week of Sep 15
$93K
Week of Sep 22
Refund small orders on its own PRD
GOAL
Resolve refunds without waiting
Eval 90+ 2 weeks after launch
+
PRDs
2 docs
One for every approved feature, written from the evidence in your customers’ signals.
Review note
Approved
UI design reviews
0 docs
Review specs and wireframes for every new interface.
Stop the agent inventing refund… Spec
Eval 81 → Eval 94
Agentic fix specs
1 doc
What broke, why, and the exact fix the agent should make.
Refund small orders on its own Eval
9
requests before launch
Post-launch evaluation specs
3 docs
Did it work after shipping? Before and after, measured.
Post-launch evaluation
Live traces
Run evaluation
EVALUATED
2
ON TARGET
1
NEAR TARGET
1
NOT LAUNCHED
1
Feature and what was checked
Verdict
Target
Result
Traces
Trend
Stop hallucinated refund policies
Agentic fixWrong policy in 31 of 1,00…
Near target
Eval 94
Eval 81 to 93
Day 14 of 14
10 failing
Reply in the customer's language
New featureSpanish and German c…
On target
+$8K / mo
+$9K / mo
2 weeks
2 failing
Let the agent refund small orders
New featureIn development
Not launched
Eval 90+
—
After launch
—
—
EVAL PASS RATE
STILL FAILING IN LIVE TRACES
High
Agent says gift cards are refundable
5 traces
Medium
Final-sale items offered a full refund
3 traces
Add follow-up to Choose
Example data
Ask anything about your product.
Query every part of your product management process in plain language — feature signals, agent behaviour, support patterns, post-launch metrics. Every answer is grounded in your live product data.
Ask
Chats
Saved
Morning!
What do you want to know?
Ask anything about your agentic product
What should we fix first to stop losing deals over refunds?
Or start with a focus
Product catalogue
Ask about one feature, its signals and status
Generate documents
Draft a PRD, brief or release note from evidence
Agentic failures
Find where your agent goes wrong
Competitor research
See what rivals ship and where you trail them
Post-launch evaluation
Check if a shipped fix hit its target
Try asking
Which agent failures came up most in chats this week?
Write a PRD for letting the agent refund small orders
Did the policy lookup fix move our eval pass rate?
What should we fix first to stop losing deals over refunds?
Start with “Let the agent refund small orders on its own”. It ranks #1 in your catalogue with a score of 88, and it is tied to $140K in lost deals.
4 of 5 competitors already offer it. It takes about 3 weeks to build, and its target is: Eval 90+ on refund tests, 2 weeks after launch.
RANK
REFUND FEATURE
SCORE
CUSTOMERS ASKED
LOST DEALS
RIVALS WITH IT
BUILD
#1
Let the agent refund small orders on its own
88
9
$140K
4 of 5
3 weeks
#2
Stop the agent inventing refund policies
48
7
–
–
2 weeks
#6
Finish returns reliably
38
4
$11K
3 of 5
3 weeks
What’s the status of “Let the agent refund small orders on its own”?
It’s in development, due Nov 2, and 1 week into a 3-week build. 9 requests and 6 lost deals ($140K) cite it,
and 4 of 5 competitors already ship it.
Let the agent refund small orders on its own
New featureIn development
9 requests · due Nov 2
Week 1 of 3
Write a PRD for letting the agent refund small orders
Here’s a draft PRD, written from the evidence behind it.
Let the agent refund small orders on its own PRD
GOAL
Resolve refunds without waiting on a person.
SUCCESS METRIC
Eval 90+ on refund tests, 2 weeks after launch.
EVIDENCE
6 lost deals · $140K4 of 5 rivals ship it9 signals
Refund orders under $50 · hand larger ones to a person with the full chat
Where does our agent go wrong most?
Invented refund policies lead by a wide margin: 31 of 1,000 chats this month. Two more show up in live traces.
Invented refund policies
31 chats
Gift cards called refundable
5 traces
Final-sale items offered a full refund
3 traces
What do rivals ship that we don’t?
Two of your refund gaps are already table stakes: most rivals automate small refunds and finish returns.
Automate small refunds
4 of 5 rivals
Finish returns end to end
3 of 5 rivals
Reply in the customer’s language
2 of 5 rivals
Did the policy lookup fix move our eval pass rate?
Yes. The eval pass rate climbed from 81 to 93 over 14 days, just short of the 94 target.
FeatureStream creates product specifications tailored to each iteration and build cycle.
PRDs (with written specs and flowcharts)
UI design reviews and wireframing
Agentic Fixes spec
Maintain and ship the best agentic products.
The problem
Most AI agent builders only learn who they’re losing to and what product feature to build next when a customer says so out loud.
FeatureStream keeps you ahead.
01
We track what's shipping.
We scan your competitors: what's launched, what's changed in the market, what's new in your category, so you're not finding out from a lost deal.
02
We show you the gap, with proof.
Not a vague score. The actual evidence. What Claude and ChatGPT say about you versus them, and exactly which feature is costing you.
03
We tell you what to build next.
A prioritised 3-month roadmap of what to build, plus a clear path to becoming LLM-visible in the use cases you want to own, so you compete where your buyers are already asking.
WHAT YOU GET
Our analytics lead you to successful outcomes
01
Product Feature Analytics
Know exactly which features get you cited. Scored across security, integrations, pricing, and capability — mapped to the use case that matters for your buyers.
02
Brand & Use Case Benchmarking
See where rivals outrank you — and why. Share of voice by use case, who owns each buying moment, and what it takes to close the gap.
03
Sentiment & Brand Coverage
Hear what LLMs actually say about you. The words, tone, and tags used when a buyer asks Claude or GPT to recommend an agent like yours.
04
LLM Visibility Playbook
Your playbook for getting cited by Claude and GPT. Grounded in what's actually indexed today through citations supported by Parallel.ai.
05
Competitive Intelligence
Continuously monitor hundreds of competitor websites, detect changes over time, and automatically alert users when a competitor ships a product feature.
