Measured in production, not in decks.
Representative engagement patterns from across the stack and the outcomes Stryki designs toward — each with a full write-up of the problem, the build, and what we'd tell you before you attempt the same.
Figures are outcomes Stryki designs toward, not guarantees; results depend on your data and workflow.
From a hypothesis to a measured outcome.
We don't count models shipped or features launched — we count the metric that moved, and we design the engagement backward from it.
Four ways the work pays back.
Time returned
Hours of judgment-heavy assembly — research, drafting, reconciliation — handed back to your team for the work only people should do.
Decisions moved earlier
Risk, demand, and churn signals surfaced before the event instead of after — so action happens while it still changes the outcome.
Cost taken out
Cheaper inference, model routing, and automation of routine volume — unit economics that improve as the system runs.
Risk controlled
Grounded answers, human gates, and audit trails — AI you can defend to a regulator, not just demo to a room.
Representative engagements, in full.
Each one is the hypothesis, the architecture, the rollout discipline, and the lessons we'd hand you before you build.
Consumer lending, decided in hours
How an underwriting agent assembles the credit file, applies policy, and drafts decisions — cutting time-to-decision by 60% while keeping a human on every approval.
Early-warning credit risk
A predictive ML program that blends bureau and behavioral signals to flag at-risk accounts before they roll — and routes the right treatment to each one.
The 6 a.m. advisor brief
Portfolio drift, suitability flags, market moves, and meeting prep — assembled by an agent overnight so advisors start the day advising, not gathering.
Tax-aware rebalancing
Drift detection across thousands of household portfolios with tax-lot-aware trade proposals an advisor reviews and approves — turning a quarterly scramble into a continuous process.
Personal quarterly commentary for forty thousand households
Grounded per-household reporting that explains what happened to this client's portfolio and why — drafted in minutes, checked against a compliance rulebook, signed by a human.
Private banking onboarding
Document AI reads the pack, verifies what it can, and assembles the file — while every screening judgment and every acceptance decision stays with a human.
Seeing assets leave before they leave
Outflows are almost never a surprise in hindsight. A model that reads the early signals — and hands advisors a specific, timely reason to make the call.
Reviewing every recommendation instead of two percent of them
Advice surveillance that reads the recommendation, the client profile, and the rationale together — flagging what a compliance officer should look at, and never issuing a finding on its own.
Prior authorization in minutes
Extraction pipelines that read patient records against payer requirements, assemble submission-ready packets, and flag gaps for human sign-off.
Trade surveillance
Legacy lexicon rules generated thousands of alerts a day and almost no findings. An agentic triage layer that correlates trading and communications, drafts a rationale, and leaves every disposition to a human.
An analyst copilot that reads everything and decides nothing
Filings, transcripts, and broker research made searchable with citations — so analysts spend their hours forming a view rather than locating the paragraph.
Post-trade breaks
Automated matching across custodian, broker, and internal records — with an agent that assembles the evidence and drafts the counterparty query for every genuine break.
The save desk that starts with context
Predictive models flag at-risk accounts; an agent assembles the full account story and drafts in-policy retention offers — reps approve, customers stay.
Support that cites its sources
A retrieval-grounded assistant that answers from the brand's own help center, policies, and live order data — deflecting routine volume and handing nuance to humans with context attached.
Forecasting demand where it's decided
From spreadsheet consensus to a governed ML forecast that planners can interrogate — fewer stockouts, less dead inventory, and a planning meeting about exceptions instead of averages.
Finding the money left in closed claims
A model plus a document agent surface missed third-party recovery in closed auto claims and draft the demand package — turning quiet leakage into recovered dollars.
The NOC's new first responder
A triage agent correlates alarms, enriches them with topology and history, and drafts resolution steps — so NOC engineers open every ticket already understanding it.
Giving clinicians their evenings back
A grounded documentation assistant drafts submission-ready notes from the encounter record, with a clinician reviewing and signing every one.
Shipping faster
How a B2B software company gave 300 engineers a copilot that actually knows their codebase, their runbooks, and their incident history — cutting ramp time and cross-team escalations.
Fifty thousand alerts a day
An agentic triage layer that enriches, correlates, and drafts a verdict for every alert — so analysts spend the night on the dozen that matter, not the twelve thousand that don't.
Invoice to cash
Document AI reads every invoice, matches it to the purchase order and receipt, and posts it — while exceptions route to humans with the evidence already assembled.
Catching defects at line speed with computer vision
A vision system that flags defects in under 200 milliseconds on the line — and, just as importantly, learns which flags the inspectors actually agree with.
Predicting transformer failures before the lights go out
Sensor telemetry, maintenance history, and weather combined into a risk score per asset — turning emergency truck rolls into planned work with months of warning.
Benefits casework
An agency cut its backlog by automating document intake and evidence assembly — while keeping every eligibility decision with a caseworker and auditing the system for disparate impact.
Four hundred thousand contracts, finally answerable
Clause extraction and obligation tracking across a decade of agreements — so legal can answer 'what are we actually exposed to?' in a day instead of a quarter.
Matching engineers to roles without letting the model decide
A talent platform that ranks and explains fit across a large candidate pool — with the model surfacing evidence, recruiters making the call, and every release tested for adverse impact.
Four thousand deliveries a day, planned in eleven minutes
Demand forecasting feeding a routing optimizer — plus a planner interface that lets dispatchers override any route, and a system that learns from every override.
Figures shown are representative of the outcomes Stryki designs toward, not guarantees; results depend on your data and workflow.
Bring us a hypothesis. Leave with a system.
Tell us what's eating your team's time. We'll give you an honest read on whether AI is the right tool — and if it is, a scoped v1 with a timeline and cost.