We build the software and AI systems your business runs on.
From AI-native products to the platforms and teams behind them, one senior practice takes the work from architecture to production. Here is exactly what we can build for you.
Four ways we plug into your roadmap.
Pick the shape that fits the problem. The engineering bar is the same across all of them.
AI Product Engineering
AI-native SaaS, copilots, RAG systems, and AI search, built into your product.
AI Automation & Workflows
Automation and internal copilots that take repetitive work off your team.
Embedded Engineering Teams
Senior, dedicated engineers embedded in your team for the long term.
Platform Modernization
Legacy modernization, cloud migration, and the infrastructure to run it.
AI Product Engineering
AI-native products built into production SaaS: copilots, retrieval systems, AI search, and the multi-tenant foundations they sit on. We ship the intelligence and the unglamorous infrastructure that keeps it reliable under real traffic.
What We Build
- →AI-native SaaS platforms, multi-tenant from line one
- →Internal AI tools and copilots for your team
- →Knowledge systems and RAG applications
- →AI search and semantic retrieval
- →Billing, RBAC, and audit foundations underneath it
Outcomes We Optimize For
- →Predictable cost-per-request at scale
- →Latency budgets that survive p99 traffic
- →Quality measured with evals, not assumed
- →Vendor-portable architecture, not lock-in
- →Observable token economics
AI Automation & Workflows
Automation that takes repetitive engineering, ops, and analyst work off your team: document processing, triage, internal copilots, and operational AI, built with the same rigor as customer-facing systems because the cost of an unreliable workflow compounds.
What We Automate
- →Document ingestion and structured extraction
- →Ticket triage and intelligent routing
- →Internal copilots for ops and analysts
- →Cross-system orchestration with deterministic fallbacks
- →Compliance and audit-trail pipelines
Where It Pays Off
- →Hours of manual processing removed each week
- →Faster turnaround on routine operations
- →Fewer handoffs and less context-switching
- →Consistent, audited outcomes you can trust
- →Cost-bounded execution per workflow run
Embedded Engineering Teams
Senior, dedicated engineers embedded in your team for the long term. The continuity of an in-house team with the flexibility of an extension. Often called staff augmentation; we run it as a partnership, not a staffing desk.
Engagement Shape
- →Dedicated developers integrated with your tools and tickets
- →Senior engineers, the same people year over year
- →Scale capacity up or down by the month
- →Attend your standups and rituals
- →Execute under your product leadership
Where It Fits
- →Long-running platform roadmaps
- →Senior gaps you cannot hire fast enough to close
- →Specialist AI and infrastructure depth on demand
- →Remote developers with a four-hour overlap with PT
- →Regulated environments needing accountable execution
Platform Modernization
Take a platform built for a smaller business and rebuild it to carry the next order of magnitude: legacy modernization, cloud migration, technical-debt reduction, and the infrastructure to run it. No freeze, no rewrite-all rewrite, no lost data or users.
Migration Patterns
- →Strangler-fig service extraction
- →Monolith decomposition with traffic-shifted cutover
- →Zero-downtime database migrations
- →Prototype-to-production transitions (Streamlit or Jupyter to Django or FastAPI)
- →Single-tenant to multi-tenant rebuilds
Infrastructure We Run
- →Kubernetes platforms with sane defaults
- →Terraform-managed multi-environment setups
- →CI/CD with deploy gates and rollback discipline
- →Observability: metrics, logs, traces, and cost
- →Cloud migration across AWS, GCP, and Cloudflare
Engineered on a production stack.
Not a list of logos. The layers we design, connect, and operate as one system.
Five steps, first call to production.
No deck-driven discoveries, no perpetual scoping. Each step has an explicit exit, so you can extend, pause, or pivot without losing context.
Discover
Working sessions with your leads. We map the system, surface constraints, and write down the scope.
Plan
A reviewed architecture: data model, topology, integrations, and risks, with a sequenced plan you own.
Build
Weekly demos and continuous deployment to staging, your team operating alongside ours from day one.
Validate
Evals, load tests, and acceptance against the criteria we set, before anything reaches your users.
Scale
Production cutover with runbooks and observability, then scale work and an optional retainer.
Proof, in production.
A few systems we built and still run. Real load, real outcomes.
Ailyze
Converted a Streamlit research prototype into a production Django SaaS with user management, integrations, and a dynamic UI.
ResInnov
Rebuilt a global market-research platform on auto-scaling, caching, and a CDN for resilience under load.
Setera
Built a custom portal for a global communications business: optimized architecture, faster load times, and a revamped UI.
Before you bring us in.
Which engagement model is right for us?+
If you have a defined AI feature or product to ship, that is AI Product Engineering. If you need to remove manual work, that is Automation. If you need senior capacity on an existing roadmap, that is an Embedded team. If your platform is straining under growth, that is Modernization. Most engagements start in one and grow into another.
Do you work fixed-bid or time-and-materials?+
Both, depending on scope clarity. The initial discovery is always fixed. Build phases are typically time-and-materials against a monthly cap, with weekly demos and the option to stop at any sprint boundary.
How fast can you start?+
Discovery within one to two weeks. Full build usually starts three to six weeks out, depending on team availability. We do not take engagements we cannot staff with senior engineers on day one.
Can you work within our cloud and compliance constraints?+
Yes. We run across AWS, GCP, Cloudflare, and on-prem for regulated industries. We sign NDAs and DPAs as a matter of course, accommodate customer paper for MSAs, and have worked under enterprise procurement before.
Do you only take AI projects?+
No. We are AI-native, but a large share of our work is platform modernization, multi-tenant SaaS, and embedded engineering. The common thread is production-grade systems, with or without an AI layer.
What does a typical engagement cost?+
Every engagement starts with a short, paid discovery. We scope the build from there, and you will always know the number before you commit. We are built for serious product work, not the lowest bid.
Let's scope what you're building.
A 30-minute strategy call. We will listen to where you are, sketch what we would do, and tell you honestly whether we are the right fit.