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One intelligent platform across 30 domains — research, finance, writing, shopping, planning — all connected, all learning from you.

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The neww.ai Intelligence Index

Eight scores. One production intelligence system.

Model intelligence alone is not the product. We measure truth, execution, reliability, and customer value — and publish the movement over time.

Intelligence
Internal baseline
82/ 100

Composite reasoning, coding, retrieval, and multimodal understanding.

30d+2 pts
90d+7 pts
Truth
Internal baseline
79/ 100

Grounded answer accuracy, citation fidelity, and hallucination resistance.

30d+3 pts
90d+9 pts
Execution
In validation
71/ 100

Ability to complete multi-step workflows end-to-end without rescue.

30d+4 pts
90d+12 pts
Reliability
Internal baseline
88/ 100

Pass rate under long tasks, retries, and production traffic.

30d+1 pts
90d+3 pts
Customer ROI
Customer pilot
74/ 100

Time saved, output acceptance, and measured business impact.

30d+3 pts
90d+11 pts
Task coverage
Internal baseline
77/ 100

Share of important customer tasks the platform completes at acceptable quality.

30d+2 pts
90d+6 pts
Latency
Internal baseline
84/ 100

Median time-to-useful-answer and time-to-completed-output.

30d+2 pts
90d+5 pts
Trust
Internal baseline
86/ 100

Auditability, source provenance, policy adherence, reproducibility.

30d+1 pts
90d+4 pts
Labels reflect evaluation maturity, not marketing tier. See methodology.
Capability radar

Progress over 90 days — every axis, at once.

Reasoning, grounded truth, coding, research, multimodal, agent execution, speed, and reliability — measured together, improved together.

Why all eight

Frontier AI companies publish a strong score on one or two axes. Real production work fails on the axis that was not measured. We publish, and improve, all eight at once.

Reasoning82·+8
Grounded truth79·+9
Coding85·+7
Research77·+9
Multimodal73·+7
Agent execution71·+12
Speed84·+5
Reliability88·+3
Calculate your ROI

See the value before you commit.

Adjust the inputs to match your team. The savings are calculated from real automation benchmarks.

Your inputs
Your monthly value
$488
$5,856 per year · 2440% return
Time saved (automation value)$433
Tool consolidation savings$75
neww.ai subscription− $20
Net monthly value$488
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Benchmark layers

Five layers. Every layer published.

Most AI companies publish one layer. Frontier intelligence is necessary but not sufficient — the system wins on truth, execution, reliability, and value too.

Layer A

Core model intelligence

The model can think, interpret, and solve.

Complex reasoning success
Multi-step reasoning tasks with verifiable answers.
Why it matters: Reasoning breadth is the ceiling on every downstream workflow.
Current
82.4%
was 75.1%
90-day change
+7.3 pts
Target
90%
Internal baseline
Code repair success
Agent-authored fix accepted on first run in sandbox.
Why it matters: Direct driver of developer productivity and trust.
Current
71.6%
was 64.2%
90-day change
+7.4 pts
Target
85%
Internal baseline
Long-context recall
Fact recall at 128k–1M tokens across mixed domains.
Why it matters: Long-context accuracy makes document and codebase work safe.
Current
88.9%
was 85.4%
90-day change
+3.5 pts
Target
95%
Internal baseline
Multimodal interpretation
Visual, document, and UI reasoning accuracy.
Why it matters: Unlocks screenshots, scanned docs, and live UI tasks.
Current
73.2%
was 66.8%
90-day change
+6.4 pts
Target
88%
In validation
Tool routing precision
Correct tool chosen for task at first decision point.
Why it matters: Bad routing cascades — it sets the ceiling on agent reliability.
Current
90.1%
was 86.7%
90-day change
+3.4 pts
Target
97%
Internal baseline
Multi-step plan quality
Human-graded plan coherence over 5+ step tasks.
Why it matters: Plans are the skeleton of long-horizon work.
Current
77.0%
was 70.2%
90-day change
+6.8 pts
Target
90%
In validation
Layer B

Grounded truth and retrieval

The system is trustworthy and grounded.

Citation fidelity
Citations that actually support the claim they are attached to.
Why it matters: The core contract for research, healthcare, finance, and law.
Current
93.2%
was 88.9%
90-day change
+4.3 pts
Target
98%
Internal baseline
Supported claim rate
Share of answer sentences anchored in retrieved evidence.
Why it matters: Unsupported claims are where hallucinations live.
Current
89.4%
was 83.0%
90-day change
+6.4 pts
Target
95%
Internal baseline
Hallucination rate
Fabricated facts per 1k generated tokens.
Why it matters: Lower is better — the single biggest blocker to enterprise trust.
Current
0.8
was 1.4
90-day change
−0.6
Target
0.3
Internal baseline
Freshness accuracy
Correctness on events within the last 24 hours.
Why it matters: Frontier models without live retrieval fail here by design.
Current
91.7%
was 86.2%
90-day change
+5.5 pts
Target
97%
Internal baseline
Retrieval precision@5
Top-5 retrieved passages judged relevant.
Why it matters: Retrieval quality sets the ceiling on answer quality.
Current
81.0%
was 74.6%
90-day change
+6.4 pts
Target
92%
Internal baseline
Source agreement
Independent sources that corroborate the stated answer.
Why it matters: Multi-source consensus is the backbone of defensible answers.
Current
2.7 avg
was 2.1 avg
90-day change
+0.6
Target
3.5
In validation
Layer C

Agent and workflow execution

The system executes, not just chats.

End-to-end task completion
Multi-tool workflows finished without human rescue.
Why it matters: Customers buy completed work — not text.
Current
71.4%
was 58.9%
90-day change
+12.5 pts
Target
90%
In validation
Tool use success
Tool called with valid args, returning usable result.
Why it matters: Reliable tool use is the atom of every agent workflow.
Current
87.8%
was 81.3%
90-day change
+6.5 pts
Target
96%
Internal baseline
Browser action accuracy
Correct DOM interaction on live pages.
Why it matters: Browser automation is the last-mile for real autonomy.
Current
68.2%
was 54.1%
90-day change
+14.1 pts
Target
88%
In validation
Recovery after failure
Runs that recover on retry without operator intervention.
Why it matters: Customers tolerate imperfect AI only if recovery is strong.
Current
76.3%
was 65.0%
90-day change
+11.3 pts
Target
92%
Internal baseline
File task pass rate
Read, edit, and synthesis tasks across real documents.
Why it matters: Documents are where knowledge work happens.
Current
84.1%
was 76.4%
90-day change
+7.7 pts
Target
95%
Internal baseline
Workflow depth
Average productive steps before first failure.
Why it matters: Depth separates assistants from agents.
Current
14 steps
was 9 steps
90-day change
+5
Target
25+
In validation
Layer D

Production reliability

The system is safe to deploy at scale.

Production uptime
Rolling 30-day availability across all regions.
Why it matters: Uptime is the precondition for every other metric.
Current
99.94%
was 99.91%
90-day change
+0.03
Target
99.99%
Internal baseline
p95 time to useful output
Median streaming first-useful-answer latency.
Why it matters: Users abandon slow systems. Lower is better.
Current
2.1 s
was 2.8 s
90-day change
−0.7 s
Target
< 1.5 s
Internal baseline
Task failure rate
Runs that terminate before producing an acceptable output.
Why it matters: Failures compound at scale — a low rate is non-negotiable.
Current
4.2%
was 7.8%
90-day change
−3.6 pts
Target
< 1%
Internal baseline
Retry recovery rate
Failed runs that succeed on automatic retry.
Why it matters: Automatic recovery keeps customers off the phone.
Current
82.6%
was 73.0%
90-day change
+9.6 pts
Target
95%
Internal baseline
Session memory stability
Context preserved across session boundaries.
Why it matters: Memory drift erodes trust faster than a raw failure.
Current
96.3%
was 92.1%
90-day change
+4.2 pts
Target
99%
Internal baseline
Concurrency resilience
Pass rate at 10× normal concurrent load.
Why it matters: Production traffic is bursty. Degraded-mode performance matters.
Current
91.0%
was 84.2%
90-day change
+6.8 pts
Target
98%
In validation
Layer E

Customer value and outcomes

The system actually creates customer value.

Average time saved
Per completed workflow vs. manual baseline (pilot cohort).
Why it matters: Time saved is the cleanest signal of real value delivered.
Current
54 min
was 41 min
90-day change
+13 min
Target
90 min
Customer pilot
Output acceptance rate
Results accepted without meaningful edits.
Why it matters: Distinguishes real utility from chat-novelty.
Current
72.1%
was 63.4%
90-day change
+8.7 pts
Target
90%
Customer pilot
Weekly workflows per user
Distinct completed workflows per active seat per week.
Why it matters: Habit formation is the leading indicator of retention.
Current
8.3
was 5.7
90-day change
+2.6
Target
15+
Customer pilot
Week-one retention
New users active seven days after first session.
Why it matters: The strongest early product-market-fit signal.
Current
68.4%
was 57.2%
90-day change
+11.2 pts
Target
80%
Customer pilot
Time to first value
From signup to first accepted output.
Why it matters: Short TTFV is the single biggest lever on activation.
Current
7 min
was 12 min
90-day change
−5 min
Target
< 3 min
Customer pilot
Cost per successful task
All-in compute + model cost per accepted output.
Why it matters: Sustainable economics is a precondition for massive adoption.
Current
$0.08
was $0.14
90-day change
−$0.06
Target
< $0.04
Internal baseline
Intelligent capabilities

AI that learns how you work — and works for you.

Intelligent price comparison — automatically finds the best deal across the web
End-to-end planning — trips, meals, budgets, and schedules optimized together
Deep research with source verification and real-time data synthesis
Adaptive writing assistant that learns your voice and style over time
Automated financial tracking with smart alerts and recurring task management
Unified context across 30 domains — your AI remembers everything, everywhere
Model and system architecture

Not a transformer. A production intelligence system.

Fast response, deep reasoning, retrieval, planning, multimodal, and evaluation models — composed into one system that the benchmark layers above actually measure.

Per-step routing
Query
Classify
Route
Retrieve
Reason
Validate
Execute
Output

Every request is classified, routed to the right model, grounded in retrieved evidence, reasoned through, validated by an independent judge, executed against the right tool, and only then returned.

01
Fast response model
Sub-second answers for routine queries.
02
Deep reasoning model
Multi-step reasoning on hard problems.
03
Retrieval + ranking layer
Grounded evidence from live web, docs, and internal data.
04
Agent planner
Decomposes goals into ordered, verifiable steps.
05
Tool-use controller
Routes each step to the right tool, API, or engine.
06
Long-context memory
Keeps working context coherent across sessions.
07
Multimodal encoder
Interprets images, documents, and live UI.
08
Domain adapters
Specialized heads for code, healthcare, finance, research.
09
Evaluator / judge model
Scores each output before it reaches the user.
10
Safety + policy filter
Constitutional checks and policy adherence.
Why neww.ai wins

One intelligent platform. Not ten fragmented tools.

Every capability built in, not bolted on. No integration tax. No vendor sprawl.

Capability
neww.ai
The old way
AI coverage
30 domains, unified intelligence
1–3 per vendor, siloed
Engine access
Full library behind one API
Limited, per-vendor contracts
Agent orchestration
Native multi-agent runtime
DIY or expensive add-on
Live web data
Built-in crawl & indexing
Separate vendor, separate bill
Search infrastructure
Integrated vector + semantic
Self-host or third-party SaaS
Enterprise security
SSO, SCIM, audit, DLP — included
Partial, often add-on pricing
Deployment flexibility
SaaS, private tenant, or VPC
SaaS only, no customization
Pricing model
Published per-call rates
"Contact sales" or opaque tiers
Why neww.ai wins

Structural advantages, not marketing claims.

OpenAI, Anthropic, Cursor, Windsurf, Perplexity, and You.com each lead on one surface. We combined the strongest lessons from each into one production intelligence system — and we benchmark the whole stack.

Advantage 01

Intelligence, truth, and execution — together

Most competitors lead in one of the three. neww.ai is scored, and shipped, across all three at once.

Advantage 02

Full-stack benchmarks, not model trophies

We benchmark the model, search, agent, workflow, and business outcome — because customers buy the system.

Advantage 03

Real customer work, not benchmark theater

Every public score is cross-checked against customer-task evals streamed from live workflows.

Advantage 04

System-level routing

Fast answers, deep reasoning, retrieval, browser, file, and code actions routed per step — not per chat.

Advantage 05

Grounded-truth infrastructure

A first-class retrieval, citation, and evidence layer — not a retrofit on top of a chat model.

Advantage 06

Cross-domain operating system

30 vertical products sharing one intelligence spine — not one feature bolted onto a chat box.

Advantage 07

Continuous eval flywheel

Customer feedback, re-ranking, and recovery loops feed every subsequent model and retrieval update.

Advantage 08

Transparent progress

Every score shows 30-day and 90-day movement. We publish trend lines, not snapshots.

The one-line differentiator

neww.ai does not benchmark only what the model knows.
neww.ai benchmarks what the full system can reliably accomplish.

Simple pricing

Start free. Scale when ready.

No credit card to start. Your work is saved when you upgrade — nothing lost.

Plus
$20/mo
  • Unlimited runs across all 30 domains
  • Intelligent task routing
  • Cross-domain context memory
  • Direct support
Start Plus
Most popular
Pro
$40/mo
  • Priority AI compute
  • Deep research & analysis mode
  • Persistent memory across sessions
  • Priority support
Start Pro
Family
$30/mo
  • Five seats included
  • Shared knowledge workspace
  • Parental controls
  • Everything in Plus
Start Family
Methodology and eval governance

Benchmark trophies are cheap. We publish the governance.

Every number on this page is tied to a benchmark definition, a run history, a refresh cadence, and a source label.

Every score is composed of named benchmarks with fixed definitions: reasoning success, citation fidelity, task completion, p95 latency, output acceptance, and cost per successful task. Each row on this page is tied to a benchmark definition and a run history.
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SOC 2 Type II
GDPR Compliant
DPA + Sub-processors
US · EU · UK Residency
99.9% Uptime SLA

Automate your day. Amplify your output.

Replace 5+ disconnected tools with one AI that remembers context across every task.

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