DEPLOYPROAI ENGINEERING · FORWARD DEPLOYED ENGINEERS
Our engineers,inside your team.
We work alongside your engineers to clear backlog and deliver production systems, not just code. Enterprise-grade, AI-native engineers, hands-on practitioners who understand your domain and can be plugged directly into your team to build, ship, and transfer working patterns.
Minimum 12 weeks inside your team, extended as needed to ship
- Embedded delivery
- Agent workflows
- Retrieval pipelines
- Voice interfaces
- LLM features
- Pattern handover
The problem we solve
The backlog has AI features on it. The team has never shipped one.
- A traditional engineer builds one capability for many customers. A forward deployed engineer builds many capabilities for one.
- Contractors deliver a repository and leave. The patterns leave with them.
- Review queues add days of idle time to every change.
- The first AI feature is being built without a governed workflow, so the second will be too.
Step 1
Goals and guardrails
Agree the outcome, the metric, the baseline, and what AI may and may not touch.
Step 2
Integrate
Set up the governed workflow in your repositories and pipelines, and pass the first change through it.
Step 3
Deliver
Ship backlog items through the loop, with every stage approved by a person.
Step 4
Evaluate and hand over
Measure against the baseline, and leave the patterns, the tests and the documentation with your team.
What we build
What we ship with you.
Agent workflows
Built to production standard in your environment, on your data, with audit trails and human escalation.
Retrieval pipelines
Ingestion, search and evaluation sets that make your documents safe for a model to read.
Voice interfaces
Inbound and outbound voice on the pattern behind the Voice Service Agent and Rehearse.
LLM features in existing products
Summaries, classification, extraction and assistants inside the product you already ship.
The governed delivery workflow
The G.U.I.D.E. loop set up in your CI, so agent-written code earns trust before it merges.
Pattern handover
Pairing, reviews and documentation, so your team continues at the same pace after we leave.
What you walk away with
Deliverables. Not promises.
Backlog items shipped to production
The governed workflow, running in your repositories
Test coverage on everything we touched
Documentation your team can maintain
A DORA and SPACE report, before and after
A team that continues without us
Production proof
Evidence before adjectives.
Two months to 48 hours
Six production modules shipped in 48 hours. The previous cycle was two months.
India's leading trading platform
Three quarters to two days
A PHP-to-Go migration planned for three quarters completed in two days, and engineering capacity was freed for product work.
A $7.5B FinTech platform
Delivered by Ashish Tripathi in prior enterprise engagements, before DeployProAI was founded. Full detail under NDA.
FAQs
Frequently asked questions
A contractor fills a seat. A forward deployed engineer ships your backlog through a governed workflow, measures the result against your baseline with DORA and SPACE, and leaves the pattern behind. The engagement ends when your team can continue at the same pace without us.
No. DeployProAI works within your own code repositories, systems and cloud accounts, and follows your security policies. DeployProAI’s Agentic Accelerators are installed in your own cloud account or on your own servers. During training, teams use the AI tools your organisation has approved, and any data is anonymised where required.
You do. Everything DeployProAI produces for you during an engagement belongs to you, including the code, the documentation and the plans. SupportSight and Rehearse, two of DeployProAI’s Agentic Accelerators, are provided under an annual licence.
Start with the outcome.
Tell us what is on the backlog and what it costs you to leave it there. We will tell you what an embedded team would ship in twelve weeks.
- NDA-first
- Your codebase
- Measured with DORA and SPACE
- GDPR
- DPDP
- SOC 2 practices
- PCI-DSS
- IRDAI-aware
- EU AI Act