Software & SaaS companies
Wizr is the AI engineering partner for SaaS scale-ups, PE-backed software companies and enterprise software vendors. We do two things, and you can take one or both.
Offering 1
More releases from the team you have.
For when the roadmap is bigger than the team. Our pods build your product with Dual Loop Engineering, alongside your engineers.
Product development in AI-enabled podsPlatform modernization and tech-debt paydownAI code generation, testing and qualityUp to 50%
Faster software delivery
Offering 2
Accelerate your AI roadmap.
For when customers expect AI in the product. Our pods take AI features from idea to general availability, built on AI Assembly.
AI features and agents inside your productData, retrieval and evaluation pipelinesModel benchmarking for accuracy and cost6 weeks
Guided pilot, measured against your own baseline
Starts with a two-week assessment covering both offerings.
The Challenge
Commitments grow faster than headcount, and hiring senior engineers takes quarters you don't have.
It comes up in renewals and competitive deals. A chatbot bolted to the side does not answer it.
A codebase built over a decade taxes each new feature and makes the platform hard to make AI-ready.
Coding assistants speed up typing, but unverified AI code adds review load, rework and defects.
Prototypes stall without evaluation, tenant isolation and guardrails — and the team hasn't shipped AI to production before.
Without benchmarking, AI features run on the most expensive model by default, and cost per request goes unmeasured.
Offering 1
More releases from the team you have. AI-enabled pods build your product alongside your engineers using Dual Loop Engineering — one loop turns requirements into precise, checkable goals; the other builds and verifies independently.
Requirements → Define Goal → Review
Define and Plan Loop
Plan, specify & iterate product & features fast
Build → Verify → Repair → Review
Build & Review Loop
Maker builds. Checker verifies independently and iteratively
Claude Code
Cursor
BMADEnd-to-end product development in AI-enabled podsAI code generation, review and automated testingPlatform modernization and tech-debt paydownAPI and integration engineeringInstead of instructing an AI agent step by step, we design a system that finds the work, acts on it, checks it and decides what comes next — continuously optimized for cost and quality.
How Dual Loop Engineering worksA separate checker agent verifies every change. The loop closes only when evidence confirms success.
A failing test, type error or broken build drives the loop forward without waiting on a person.
They state intent precisely and stay accountable for what ships. Standards and architecture travel with every agent.
Offering 2
Accelerate your AI roadmap. A product pod takes each AI feature from idea to general availability, starting from pre-built AI Assembly components instead of a blank page. You own what ships.
Copilots, semantic search, natural-language analytics and agentic workflows.
Pipelines, embeddings and retrieval over your product's data, so features answer from each customer's own context.
Accuracy, latency and cost per request measured; models benchmarked and right-sized before release.
Pick the use case
Where AI changes what your customer can do
Prototype
A working feature on your data, in your product
Evaluate
Golden sets and model benchmarks
Harden
Guardrails, tenant isolation, audit trail
Release
General availability, with monitoring
Dedicated AI and software engineers that join your sprints and flex with the roadmap.
Lower cost to serve with agents that resolve customer queries from your knowledge base and ticket history.
One register of every agent you run — internal and in-product — with accuracy, cost and risk tracked.
Ship more without growing headcount at the same rate, and add AI features that lift expansion and retention.
Deliver the value-creation plan: faster roadmap, a credible AI story at exit, and board-ready metrics.
Modernize mature platforms and add agents with the security, tenancy and audit your customers require.
Turn domain data into differentiated AI features for healthcare, education, logistics and more.
How an engagement runs
We baseline from your own repositories and tickets in week one. A weekly scorecard decides whether we scale.
Weeks 1–2
Read the codebase, pipeline and backlog. Set a delivery baseline, pick a pilot team and an AI feature candidate.
Weeks 3–8
Dual Loop Engineering on one team, an AI prototype on your data, and a go or no-go at week six.
Months 3–6
Dedicated pods take roadmap items, and the first AI feature reaches customers.
Ongoing
Pods flex with the roadmap, new AI features enter the pipeline, with quarterly leadership reviews.
What you measure · Offering 1
What you measure · Offering 2
Explore our case studies to see how Wizr is helping enterprises drive measurable
transformation with AI.
FAQ
No. Each stands on its own. When you take both, they share one assessment, one team lead and one weekly scorecard.
You do. Everything built in the engagement, including AI features and prompts written for your product, is assigned to you.
Pods join your sprints, repositories and ceremonies. We take whole roadmap items so ownership stays clear between teams.
Claude Code, Cursor and BMAD today, connected to Jira, GitHub or GitLab and your CI/CD.
Wizr is SOC 2 Type II and ISO 27001 certified and GDPR compliant, with least-privilege access and encryption in transit and at rest.
The assessment and pilot are fixed-price. Pods are priced per month, per pod.
You get a delivery baseline, one pilot team and one AI feature candidate. If the numbers are not there at week six, you stop.
Book a 6-week pilot
