Forward Deployed Engineering

Agentic AI that works.

TrueFoundry FDEs work with your teams to take AI applications from prototype to production — helping you design, deploy, scale and operate agentic AI systems on your own infrastructure.

See success stories

$100M+

Value delivered

3–6 wks

To working prototype

4 Offices

San Francisco, Boston, London, and India

Who we are

We own AI systems end-to-end — from architecture to outcomes.

TrueFoundry's Forward Deployed Engineering team embeds with enterprise teams to take AI, ML, and agentic systems from architecture to production. We're accountable for what we ship.

Success stories

Delivering high-impact enterprise outcomes

A selection of agentic and AI systems we've shipped — and the business value behind them.

User-Friendly Agentic IVR

A Fortune 100 retailer launched an LLM-driven IVR for 10k+ stores, handling 500M+ calls/year at <2s latency.

$50M+ annual cost savings
10–15% containment boost
Full value in 4 months

AI-Powered OCR for Specialised Industries

Digitising handwritten and faxed prescriptions (20% of 200M annual volume) using a Gemini multimodal pipeline.

Concept → production in 12 weeks
>99% extraction accuracy
$7M pharmacist time saved

Multi-Agent LLM for Cluster Observability

With NVIDIA — a multi-agent observability system spanning hybrid and multi-cloud environments hosting OSS LLMs.

6-week POC
Production in 6 months
$10M+ from optimised cluster use

AI Shopping Assistant Chatbot

An AI shopping assistant on a retailer's web + iOS app, integrated with internal data for availability, specs, reviews, and checkout.

6 weeks to launch
100% user rollout
85k MAU · 120k+ conversations/mo

Predictive Prior Authorization

A proactive ML system evaluating millions of pharmacy claims pre-adjudication across ~10,000 pharmacies, feeding an auto-fill + auto-submit pipeline.

CatBoost on ~5M rows
98% accuracy · 91% recall
Live integration

Agentic Pharmacy Claim-Reject Resolution

A real-time agentic workflow recommending the Next Best Action grounded in payer policy and technician-resolution history.

Qdrant RAG over payer policy
Citation-grounded reasoning
Live in shadow mode nationwide

Agentic Browser Automation for Booking

An agent that navigates pre-approved third-party sites to find and book doctor appointments without leaving the client's app.

Goal-driven UI interaction
Lifecycle: search → book → reschedule
Handles CAPTCHAs & gatekeepers

Agentic Research System for Sales

Combines Fireflies meeting transcripts with Salesforce data for deep research on high-value accounts.

Multi-agent planning + critique
Topic extraction + semantic retrieval
Evidence-grounded answers

TrueMem — Model-Agnostic Memory Layer

Dual-architecture memory separating short-term context from long-term user facts, with semantic dedup and parallelised retrieval.

<45ms context prep latency
Zero vendor lock-in
Async progressive summarisation

Hybrid Intent Classifier (Contrastive + RAG + LLM)

Contrastive embedding fine-tuning + RAG grounding + LLM resolution for domain-specific intent classification with scarce labels.

+40% over baseline · 88–92% acc.
~30% fewer misrouted queries
~65% faster onboarding

Why work with us

Why enterprises choose us

Four reasons enterprise teams trust us with their most important AI work.

Embedded ownership, not staff augmentation

Our engineers work inside your team and own the AI subsystems they deliver — architecture, build, deployment, and outcomes. A senior team you can hold accountable, not contractors you have to manage.

Specialised in enterprise AI

GenAI, traditional ML, and agentic systems built for enterprise scale. We focus on the AI/ML/agentic subsystems most teams find hardest — and we bring deep, current expertise in patterns that ship.

Shared DNA with TrueFoundry's platform team

We're trained and work closely with the engineers behind TrueFoundry's AI Gateway and Deployment Platform — used in production by NVIDIA, Cargill, ResMed and hundreds more.

Proven time-to-value

Working prototypes in 3–6 weeks. First production deployment in 1.5–3 months. Benchmarks set by 20+ enterprise projects delivered over the past two years.

What we deliver

Six ways enterprise teams engage us

From a two-week prototype to long-running AI infrastructure management.

Product & feature delivery

AI system architecture and design

We design the architecture for the AI system you're about to build — components, data flows, model choices, infrastructure, integration patterns. Your team implements; we set the foundation right.

Rapid prototyping for business-case validation

A scoped, paid engagement to build a working prototype that proves — or disproves — a business case before you commit to a full build.

Start-to-finish product or feature delivery

End-to-end ownership of an AI-powered product or feature, from discovery and architecture through deployment and post-launch support.

High-impact AI and agentic components

We deliver the AI/ML/agentic engine inside your product. Your engineers own the application, UX, and integration; we own the AI core.

Platform & infrastructure

TrueFoundry platform installation & customisation

Installation, customisation, and integration of the TrueFoundry AI Gateway and AI Deployment Platform inside your environment.

AI infrastructure management & automation

Ongoing operation, optimisation, and automation of your AI infrastructure — model serving, gateways, observability, and cost controls.

Time-critical engagement? Any of these can be delivered in 24/5 follow-the-sun mode, supported by our teams in San Francisco and India.

Technical capabilities

What we're good at

Six capability areas where our team has shipped enterprise systems.

GenAI and LLM systems

Retrieval-augmented generation, prompt engineering, fine-tuning, and evaluation pipelines for production LLM workloads — where retrieval quality, latency, and grounding accuracy are non-negotiable.

Try it

Intelligent Document Processing accelerator

Read more

TrueFoundry Accelerator Series: Intelligent Document Processing

AI agents and agentic systems

Multi-step agents, tool use, planning, and orchestration — the patterns that turn LLM calls into systems that get work done, with the safety and observability production demands.

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Calendar Scheduling Agent accelerator

Read more

TrueFoundry Accelerator Series: Calendar Scheduling Agent

Traditional ML

Classical ML for problems where it still wins — classification, ranking, forecasting, recommendations — trained, evaluated, and shipped with the rigour the use case requires.

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Intent Classification with SetFit accelerator

Read more

Building Enterprise-Grade Intent Classification with SetFit

AI/ML infrastructure & MLOps

Model serving, deployment pipelines, gateways, observability — the production scaffolding that lets AI systems run reliably, drawn from the platform engineering we sit alongside daily.

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MCP Gateway / data querying accelerator

Read more

Querying Structured & Unstructured Data Seamlessly with MCP Tools

Model optimisation & inference economics

Latency reduction, throughput tuning, and cost optimisation for production AI workloads — where small percentages of unit economics decide whether a system scales.

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Inference optimisation accelerator

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Optimising LLM inference for production

Tool-agnostic by default

Our team is tool-agnostic by default — we work inside our clients' stacks and within their architectural decisions. When clients hire us to own the architecture, we choose the tools that fit the problem and the team that will run it.

Project delivery

How we deliver

Two models, depending on whether the project sits inside your team or with ours.

Embedded delivery

Our engineers join your team and work through your processes — your project leads, your backlog, your sprint cadence, your tooling. No parallel process, no overhead.

Best for teams that have the engineering process they want and need specialist capacity inside it.

End-to-end delivery

We own the project from scope through production. Delivery runs through our internal SDLC, shared and confirmed before kick-off — visibility without day-to-day ownership.

Best for teams that want outcomes delivered rather than capacity added.

Our people

Senior operators leading every engagement

Co-founder & CEO of TrueFoundry — enterprise platform for building, deploying, and governing AI/LLM applications at scale
Former Machine Learning Tech Lead at Facebook — launched FB Messenger's first on-device model and led the Proactive Assistant
Previously ML Tech Lead at Reflektion and co-founder/CEO of EntHire; deep expertise in production ML systems and AI platform strategy

Facebook Reflektion EntHire TrueFoundry

12 years across strategy consulting, product management, GTM, and supply chain / manufacturing operations
3 years at Bain advising F500 clients and PE funds on AI/GenAI adoption strategy
MIT MS/MBA with prior domain experience in healthcare and retail / eCommerce

MIT Abbott Bain & Company Amazon

6 years in AI product development — concept, cost, requirements, architecture, IP, launch
12 years in drug discovery, high-throughput screening, and big-data analysis
Inventor, product lead and system architect for products generating $100M+ revenue

Amazon GE HealthCare LivePerson

Our engineering team

Senior developers across AI, backend, data, frontend, DevOps, and MLOps

Jitender Kumar

Senior Data Scientist
Gaurang Rokad

Senior Software Engineer
Kashish Kumar

Senior ML Engineer
Praharshit Gorripaty

Senior Software Engineer
Prathamesh Saraf

Senior Software Engineer
Rishikesh Anand

Senior Software Engineer
Sourav Gupta

Senior Software Engineer
Ram Kamra

Senior Site Reliability Engineer
Saakshi Ghai

Senior Software Engineer
Ketan Gangal

Senior Devops Engineer
Dennis Ahuja

Senior Devops Engineer
Manoj Reddy Bedadhala

Senior AI Engineer

Contact us

Let's discuss what you're trying to build.

Whether you have a defined project, an early idea, or just want to understand what's possible — a 30-minute call is the right first step.