Northwind builds AI that ships.Not just demos.

Northwind®

Northwind is an AI company that builds and runs the systems behind production.

Agents, retrieval, document pipelines and forecasting: shipped, monitored and owned by your team.

02 Agents

Agents that finish the job.

Multi-step agents with tools, retries and a human checkpoint where it matters. Every action is logged, typed and reversible.

91%Straight-through
4.2 sMedian run
Agents & orchestration
03 Evaluation

Proven before it ships.

Every release is scored against a gold set, watched for drift and rolled back in one click if it slips.

94.2%Grounding accuracy
99.95%Uptime
Evaluation & monitoring

Northwind builds AI that ships.Not just demos.

Northwind®
Northwind

Northwind is an AI company that builds and runs the systems behind production.

Agents

Agents that finish the job.

Multi-step agents with tools, retries and a human checkpoint where it matters. Every action is logged, typed and reversible.

Trusted in production by

Meridian Trust

Alderleaf

Cobalt Mutual

Ferrovia

Northfield & Cole

Hearn Whitby

The platform

Six layers.
One platform.

Everything an AI product needs, built to work together.

  1. Connect every source in minutes, with lineage on every field.

04 · Proof

Before → after, in production

Numbers from systems

Numbers from systems

that are still running.

that are still running.

01

Meridian Trust Bank

Financial Services

Avg. loan-file review

1.5 h

Was

4.1 h

−63%

Loan-file review cut 63% with agents

that know when to stop.

Underwriters were re-keying the same fields across four systems. An agent now does the cross-checking and flags only what needs a human decision.

$2.1M

Annual cost avoided

0.62

Review threshold, conf.

9 wks

Kickoff to production

Read the case

01

Meridian Trust Bank

Avg. loan-file review

1.5 h

Was

4.1 h

−63%

Loan-file review cut 63% with agents

that know when to stop.

Underwriters were re-keying the same fields across four systems. An agent now does the cross-checking and flags only what needs a human decision.

$2.1M

Annual cost avoided

0.62

Review threshold, conf.

9 wks

Kickoff to production

Read the case

02

Alderleaf Health Network

Healthcare & Life Sciences

Straight-through intake

91%

Was

0%

+91 pts

Clinical intake that clears itself

before staff sit down.

Referral letters, lab results and insurance forms are extracted, validated against the patient record and routed across 14 clinics.

4,200 h

Staff hours saved / month

14

Clinics onboarded

14 wks

Kickoff to production

Read the case

02

Alderleaf Health Network

Straight-through intake

91%

Was

0%

+91 pts

Clinical intake that clears itself

before staff sit down.

Referral letters, lab results and insurance forms are extracted, validated against the patient record and routed across 14 clinics.

4,200 h

Staff hours saved / month

14

Clinics onboarded

14 wks

Kickoff to production

Read the case

03

Cobalt Mutual Insurance

Insurance

Avg. claims handling

13 min

Was

21 min

−38%

A claims assistant that answers

with its sources.

Adjusters ask in plain language and get answers grounded in policy wording and past decisions, each one cited.

+27 pts

First-contact resolution

94%

Grounding accuracy

10 wks

Kickoff to production

Read the case

03

Cobalt Mutual Insurance

Avg. claims handling

13 min

Was

21 min

−38%

A claims assistant that answers

with its sources.

Adjusters ask in plain language and get answers grounded in policy wording and past decisions, each one cited.

+27 pts

First-contact resolution

94%

Grounding accuracy

10 wks

Kickoff to production

Read the case

04

Ferrovia Logistics

Manufacturing & Logistics

Forecast error (MAPE)

12.5%

Was

18.9%

−6.4 pts

Forecasts that say when

they are losing accuracy.

Demand models across 22 distribution centres, monitored for drift and retrained on a schedule the planners can see.

−22%

Safety-stock cost

22

Warehouses

16 wks

Kickoff to production

Read the case

04

Ferrovia Logistics

Forecast error (MAPE)

12.5%

Was

18.9%

−6.4 pts

Forecasts that say when

they are losing accuracy.

Demand models across 22 distribution centres, monitored for drift and retrained on a schedule the planners can see.

−22%

Safety-stock cost

22

Warehouses

16 wks

Kickoff to production

Read the case

06 · In their words

Operators, not buyers

Renee Castellano

Meridian Trust Bank

Dr. Aaron Mbeki

Alderleaf Health Network

Lindsay Oduya

Cobalt Mutual Insurance

Tom Baptiste

Ferrovia Logistics

Whitney Sarr

Orinda Freight Co.

“

We didn’t want a black box making credit decisions, and Northwind didn’t build us one. The agent does the tedious cross-checking and tells us exactly why it flagged what it flagged. Our underwriters trust it because they can see its work.

Renee Castellano

VP of Loan Operations · Meridian Trust Bank

−63% review time

07 · Engagement models

From $18,000

Assess, prove, scale,

then keep it running.

Assessment

Know what to build

Teams with an AI budget and no shared way to prioritise between use cases.

From

$18k

2–5 weeks

Data & infrastructure audit

Use-case matrix: effort, risk, payback

Build-vs-buy per use case

12-month roadmap with budget bands

Pilot

Most popular

Prove it works

Teams with a specific use case who need to prove it before a full build.

From

$65k

6–10 weeks

One system, scoped to ship fast

Evaluation harness before launch

Guardrails and human checkpoints

A clear go / no-go on scaling

Scale

Run it for real

Teams taking a proven use case to full production volume.

From

$180k

3–6 months

Full engineering team

Monitoring and alerting from day one

Integration with systems of record

Runbooks and an agreed handoff

Retainer

Keep it accurate

Teams who want us to keep operating a system after launch.

From

$12k

per month

Drift detection and monitoring

Scheduled eval and retraining

Incident SLA

Quarterly roadmap review

08 · Questions

Before you book a call

Straight

answers.

Still unsure where your use case sits? A 30-minute readiness call usually settles it.

General

Fees & contracts

Data & security

01

How is Northwind different from hiring an in-house AI team?

You get a team that has already shipped 64 systems and knows where the gap between demo and production is, without the 6–12 months it takes to hire and ramp an internal team.

02

Do you build custom models or use off-the-shelf ones?

03

We tried an AI pilot that went nowhere. What is different?

04

What happens after the system goes live?

Production AI
for every workflow

09 · Start

09 · Start

Ship the one

that matters.

Tell us the workflow. In 30 minutes you’ll know whether it’s ready to build, and what it would take.

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