Hirebolt
Backed byY Combinator

Turn AI models into working products.

Hirebolt helps teams move from ideas to working AI. We handle model selection, integration, and engineering so you can ship AI copilots, agents, RAG systems, and automation that drive business results.

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Vetted AI engineersFrom pilot to productionKPI-aligned systemsFull code & IP ownership

Strategy to action

~7 days to align on your technical roadmap and deploy an active engineering pod.

Engineering depth

Top 1% vetted software, machine learning, and infrastructure developers.

Proven delivery

97% first-match precision for specialized engineering teams.

Bring AI into everyday work

Whether you're adding AI to existing products, scaling pilots to production, or building AI-first products from scratch, we bring the engineering capacity and specialist depth you need.

Identify where AI creates real value, align your team around the right priorities, and build a practical roadmap before investing heavily in development.

Use case discoveryAI readiness assessmentRoadmap definitionSuccess metrics

Challenges we solve

AI pilots succeed in isolation but never scale because the broader organization isn't aligned or ready.

Teams jump into building before validating whether the use case is technically feasible or commercially worthwhile.

Lack of internal alignment regarding data posture, system maturity, and technical constraints.

Our solution

Assess readiness: Evaluate where your organization stands on data quality, infrastructure, and team alignment before committing to a direction.

Identify the right use cases: Prioritize opportunities based on feasibility, business impact, and what your team can realistically deliver.

Build a shared roadmap: Align business and technical stakeholders on what gets built, in what order, and what success looks like.

Define outcomes upfront: Set clear metrics tied to business value, not just model performance, before a single line of code is written.

Embed vetted AI engineers, ML specialists, and product teams directly into your workflows, tools, and standups to help you ship faster.

AI & ML engineersLLM & RAG developersAI product teamsData & MLOps engineersTechnical evaluators

Challenges we solve

The roadmap is clear but the internal team doesn't have the bandwidth or specialist depth to execute it.

Internal teams are capable but stretched too thin to handle specialized machine learning infrastructure.

Hiring senior AI engineers through normal channels takes months and often misses the mark.

Our solution

Vetted for AI depth: Every engineer is assessed for hands-on experience with LLMs, RAG, fine-tuning, agents, and production AI systems — not just general software skills.

Integrated from day one: Engineers work inside your tools and workflows immediately. No long onboarding cycles, no external handoffs.

Flexible team structure: Seamlessly expand from a single engineer to a full development team without losing project context or trust.

Proven at production scale: Access engineers who have shipped complex model deployments and cloud infrastructure at scale.

Design and build production-ready AI applications that fit naturally into existing workflows and deliver measurable results.

AI copilots & assistantsAgentic workflowsRAG systemsInternal AI toolsCustomer-facing AI products

Challenges we solve

Prototypes work in demos but fall apart under real usage, real data, and real scale.

Internal teams have the vision but not the specialist capacity to execute end to end.

Fearing dependency on rigid, expensive third-party platforms that restrict code access.

Our solution

Validate before you build: Test feasibility and early ROI with a scoped prototype before committing to a full development cycle.

Build alongside your team: Our engineers embed in your workflows to reduce handoffs and keep delivery moving without gaps.

Engineer for production: We build with reliability, latency, cost, and maintainability in mind from the start.

You own everything: Your company keeps 100% control over all code repositories, intellectual property, and model data.

Keep your AI systems accurate, efficient, and aligned with how your business uses them. Shipping is the beginning, not the end.

Prompt optimizationModel behavior tuningEvaluation loopsCost and latency improvementsCapability expansion

Challenges we solve

Model accuracy drifts over time as real-world data diverges from training conditions.

Infrastructure and API token expenses grow exponentially as more users enter the system.

Systems that worked well at launch start underperforming as requirements evolve.

Our solution

Continuous monitoring: Track accuracy, latency, and cost across live systems so issues are caught early and addressed before they affect users.

Prompt and behavior refinement: Systematically improve model outputs through structured evaluation, feedback loops, and prompt optimization.

Model fine-tuning: Update and adapt models with new data to maintain performance as your domain and use cases evolve.

Cost and efficiency optimization: Reduce inference overhead and improve response quality without trading one for the other.

AI products
we help build

AI agents & copilots

Develop autonomous assistants that handle complex multi-step reasoning, accurate function-calling, and secure codebase interaction.

Advanced RAG systems

Build high-precision Retrieval-Augmented Generation architectures to safely query dense enterprise documentation without data leaks.

Workflow automation

Replace manual operational friction with intelligent background routines that parse files, synthesize logs, and update databases.

Document intelligence

Extract structured, reliable data matrices out of noisy, unstructured enterprise files, PDFs, images, and long-form text logs.

Predictive models

Deploy custom analytical frameworks to capture domain-specific patterns, evaluate risk scores, and assist complex operational decisions.

Multimodal & voice systems

Build interfaces that smoothly process speech, visual maps, and complex UI layouts for real-time customer and internal platforms.

How it works

How we co-create
your AI systems

Simple steps to design, build, and improve AI systems.

Scope & align

We review your existing stack, product goals, and constraints. Together we define a clear MVP, set performance benchmarks, and agree on what the team needs to deliver it.

Integrate & ship

We deploy top 1% AI talent into your workflows with the stack and models that fit. Team codes prototypes, builds data pipelines, hooks models into your infrastructure around your KPIs.

Monitor & refine

Once live, we keep improving. Model behavior gets refined, performance is monitored, and new capabilities are added as your product and requirements grow.

Why Hirebolt

Engineering-led.
Outcome-focused.

Simple steps to design, build, and improve AI systems.

1.

We build alongside you

Our engineers join your standups, use your tools, and stay aligned with how your team works day to day. No handoffs, no work happening in a black box somewhere else.

2.

AI-native engineers, not generalists

Every engineer is vetted for hands-on AI experience: LLM integration, RAG systems, agent development, fine-tuning, and production monitoring. We don't place generic developers on AI projects.

3.

Total support for the full product

Start with one specialist and scale to a full team as the project grows. We cover every role in the AI product stack: ML engineers, full-stack developers, data engineers, and MLOps specialists.

4.

You own everything

All code, model weights, fine-tuning outputs, and text data stay 100% yours. We work inside your systems and infrastructure. No vendor lock-in and no proprietary platforms.

Have an AI project in mind?

Partner with Hirebolt to scale your development capacity, build resilient AI integrations, and ship secure AI products.

Start a projectTalk to an expert