Production AI and SaaS engineering for companies that can’t afford fragile systems.
We help healthcare, FinTech, and B2B SaaS companies take AI to production, repair unstable architecture, and add senior delivery capacity — without hiring a large internal team.
- production systems shipped
- 34
- production systems shipped
- median engineer experience
- 8+ yrs
- median engineer experience
- typical engagement
- 6–12 mo
- typical engagement
Three expensive problems, solved.
Take an AI prototype into production
The demo works; production is a different sport. We add the guardrails, human-review loops, evaluation, monitoring, and cost control that let an AI feature survive real users — and compliance review.
Fix unstable SaaS architecture
Performance decay, multi-tenant leaks, a legacy framework nobody dares touch. We modernize incrementally — no rewrite freeze, no big-bang cutover — so the roadmap keeps moving while the foundation gets solid.
Add senior capacity without mass hiring
Senior engineers embedded in your team, contributing within two weeks — carrying the roadmap while you recruit, or as the long-term delivery arm you don’t have to manage into existence.
Three ways in. Clear prices.
Most engagements start with the audit — it is easier to approve than a six-month contract, and the findings stand on their own.
The low-risk first step
AI & Architecture Audit
$3K–$7.5K1–2 weeks
A fixed-scope review of your architecture, AI risks, security posture, and scalability — delivered as written findings ranked by risk, with a prioritized remediation plan.
How the audit worksOne workflow, done properly
Production AI Build Sprint
$15K–$40K4–8 weeks
Build or stabilize one important AI workflow — with guardrails, human review, evaluation, and monitoring — from working prototype to something you can put in front of customers.
What a sprint coversLong-term delivery capacity
Embedded Senior Engineering Team
$20K–$60K/mo6–12+ months
Senior engineers embedded in your team for ongoing architecture and product delivery. Your roadmap, your codebase, your ownership — our capacity.
How embedding worksSystems we keep in production.
A snapshot of the platforms, automations, and AI products our teams build and maintain today.
- 01MarketingOngoing
AI Voice Agents for Inbound & Outbound Campaigns
US marketing company
Manual dialing and follow-up capped how many prospects the team could reach, and missed inbound calls meant lost opportunities — aI voice agents on Twilio and Vapi that run outbound campaigns and answer inbound calls, with automated voicemail drops and SMS follow-ups.
Outcomes- AI agents covering both inbound reception and outbound campaign calls
- Automated voicemail drops and SMS follow-up on unanswered calls
- 02HealthcareOngoing
AI Clinical Documentation Platform
US healthcare provider (confidential)
Physicians were losing hours per day to manual documentation, and off-the-shelf AI scribes could not integrate with the existing records workflow or meet compliance requirements — an AI-assisted documentation platform that drafts structured clinical notes for physician review, integrated with the existing workflow and built HIPAA-aware from the first commit.
Outcomes- 60% reduction in physician data-entry time
- Human review required on every AI-generated note
- 03B2B SaaSOngoing
Document Intelligence at 50,000-PDF Scale
B2B data platform (confidential)
Tens of thousands of vendor PDFs in inconsistent formats made the client’s most valuable data effectively unsearchable — and answers without source citations could not be trusted — a normalization and validation pipeline feeding a search platform where every result carries citations back to the exact source pages.
Outcomes- ~50,000 PDFs ingested, normalized, and made searchable
- Validation pipeline with quarantine for malformed documents
Healthcare first. Complex B2B always.
We deliberately don’t serve every industry. Depth in a few regulated, failure-intolerant domains beats breadth in all of them.
- 01
Healthcare
Our deepest wedge — AI that survives compliance review.
Clinical documentation (60% less physician data entry), patient portals, billing workflows, dental AI, document intelligence — all built HIPAA-aware: human review on AI output, access controls, audit trails.
- 02
FinTech
Systems where a wrong answer costs real money.
Multi-tenant platforms, reconciliation and data pipelines, AI with evidence trails — engineered for auditability and the failure modes that finance actually punishes.
- 03
B2B SaaS
From prototype to platform without the rewrite.
Document intelligence at 50,000-PDF scale, multi-tenant voice AI, legacy performance modernization — production systems that keep shipping while the architecture improves underneath.
Founder-led
Every engagement is led by our founder, Temurjon M. — 17 years of engineering, and the person you meet on the first call is the person accountable for your architecture.
We are not for everyone.
Radical transparency saves both of us time. Here is when we are not the right fit — and when we are.
Not the right fit if
- Your budget is under $10K
- You need this done in under 4 weeks
- You are not technical and cannot evaluate our work
- Your data is locked behind compliance you cannot navigate
- You need 24/7 on-call support
A strong fit if
- You have $10K+ budget for this initiative
- You can give us 6–8 weeks to do this right
- You have a technical stakeholder to partner with
- You want ownership of the codebase when we are done
- Your data is accessible, or you can get access
- You need production-ready systems, not experiments
Not sure which column you are in? That is what a 30-minute call is for.Schedule a feasibility call
In their words.
Client feedback from engagements via our Upwork agency profile — Top Rated Plus, 100% job success.
“They have a strong command of LLM architecture and modern web stacks, and were able to translate the complex requirements of my projects into clean, scalable implementations. Resourceful, responsive, and dependable — I would not hesitate to recommend them for advanced AI, LLM, or full-stack development work.”
“They took direction from our senior engineers exceptionally well, while also offering valuable technical suggestions of their own. Their ability to adapt quickly and contribute meaningfully made them an invaluable partner.”
“The AI consulting and strategy work helped us navigate complex technology decisions. Their expertise saved us months of research and trial-and-error.”
Tell us what you’re building.
A 30-minute feasibility call. We will tell you honestly whether we can help — and if we cannot, we will point you to someone who can.
Asked before every kickoff.
Candid answers on scope, velocity, and governance so your team can align quickly.
How quickly can you get a production-ready pilot live?
Most well-scoped pilots ship in 6–8 weeks. If we miss that window because of our planning, we absorb the additional engineering time required to cross the finish line.
What does onboarding look like for new engagements?
Every project begins with a collaborative workshop where we map success metrics, data constraints, and compliance requirements. Within five business days you receive a delivery roadmap, resourcing plan, and integration checklist.
How do you handle security and compliance for AI products?
Security runs alongside delivery: SOC 2-aligned controls, HIPAA-ready data handling, threat models, and review rituals built into each sprint. Documentation ships with the code so procurement and legal stay in lockstep.
Do you support internal team enablement after launch?
Yes. We embed dashboards, runbooks, and enablement sessions before transition. Most clients retain us in a co-sourced capacity for a quarter while their teams take ownership.