Diffco Services

Develop AI into your product

AI/ML, RAG, computer vision, and copilots, engineered to production standards by senior engineers and AI agents working to a plan.

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  • LLM/ML
  • Image/Video generation
  • Computer Vision
  • Audio Recognition

What we build

Custom AI agents & copilots

Custom AI agents, copilots, and multi-agent systems for sales, support, ops, and research. Production-grade from day one.

RAG & Knowledge AI

Vector pipelines, semantic retrieval, source-grounded answers. Turn your private data into a competitive moat.

Predictive & ML systems

Forecasting, anomaly detection, scoring, and personalization.

Computer vision

Image and video understanding, quality control, document processing.

AI platforms & MLOps

Production pipelines, monitoring, governance, and observability.

What we bring

Tech stack

AI models

  • Anthropic
  • OpenAI
  • Gemini
  • Hugging Face
  • Mistral
  • Qwen
  • Grok
  • Kimi AI
  • TypeSafe AI
  • Open weight models

Eval & testing

  • OpenAI
  • LangChain
  • Helicone
  • Promptfoo
  • Ragas

Frameworks

  • LangChain
  • LlamaIndex
  • MCP
  • Function Calling

Retrieval

  • Pinecone
  • Weaviate
  • pgvector
  • Qdrant

AI Voice

  • ElevenLabs
  • Deepgram
  • Whisper

AI-accelerated work

  • Claude Code
  • Cursor
  • Internal prompt-management
  • automated competitive scanning

Don't see your stack?

Our process isn't tied to any one model or framework, so we adapt to yours and upgrade as better tools arrive.

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Diffco AI Methodology

A delivery method built for the AI era, not retrofitted to it.

Code is the cheap part now. Knowing what to build first, which foundation will hold at ten times the users, and what not to build at all is where projects are won.

Senior engineers make those calls. More than 100 AI agents per engineer do the building, around the clock, on our own delivery platform built on Claude Code and OpenAI Codex. A living plan with automatic checks keeps every agent inside the lines.

  • You click through your product before we build it
  • We bring you the parts of the job you never put into words
  • Every architecture decision is written down with the alternatives
  • Everything traces back to a goal, which is what makes change fast
  • People make the decisions, and AI agents build inside them
  • Before release, a person watches it work
  • The whole project
    is a document you can read
  • Read the full methodology

Integrations

Built into your existing environment

AI model providers

OpenAI, Anthropic, Google Gemini, Mistral, OpenRouter, Vercel

CRM / ERP

Salesforce, HubSpot, Pipedrive

Data platforms

Snowflake, BigQuery, Databricks, Redshift

Communication APIs

Twilio, SendGrid, Sendbird

How we build

Seven stages, with a person signing off at every gate.

Every project runs through Production-Ready AI Engineering: seven stages, senior engineers directing 100+ AI agents, a check on every save, and a person signing off at every gate.

  1. 01

    Discover

    Human + AI

    Workshops and stakeholder interviews with AI in the room. It cross-verifies inputs across calls, docs, and Slack threads, flagging blind spots, edge cases, and contradictions humans miss.

  2. 02

    Plan

    AI

    AI decomposes the work, picks architecture, models, and tools. Surfaces risks, costs, trade-offs, and conflicts between stated requirements, before they become bugs.

  3. 03

    Align

    Human

    You review and approve. Every decision is logged: an auditable trail before any code is written. No black box, no scope drift.

  4. 04

    Build

    Human + AI

    AI agents execute the approved plan inside engineered guardrails. Senior engineers steer and unblock. Sprint cadence with working artifacts, not status decks.

  5. 05

    Validate

    Human + AI

    Three independent layers on every release candidate: automated evals, senior code review, and dedicated Human QA, with manual and exploratory testing alongside security, performance, and accessibility checks.

  6. 06

    Release

    Human + AI

    Production deployment, UAT, knowledge transfer, runbooks. Cutover is documented, reversible, and on a schedule you approve. Your team takes the keys, or we operate it for you.

  7. 07

    Evolve

    Human + AI

    Launch is a milestone, not a finish line. Monitoring, feedback loops, and incremental improvements keep the system compounding, and feed the next discovery cycle.

Every later change re-enters the same loop, and nothing skips a step.

Read the full methodology

Engagement models

Ways to work with us

Dedicated Team

Human-led, AI-assisted · Monthly commitment

A senior squad reserved for you on a monthly basis, using AI to move faster. Best for evolving products and complex domains. You get:

  • A senior team that’s always yours, never reassigned mid-project
  • Scope and priorities you can flex sprint by sprint
  • Predictable monthly spend with no padding for risks you may never use
  • Velocity from a team that already knows your codebase

Agent-Led Delivery

AI-built, senior-directed · Monthly commitment

Most of your monthly budget goes into AI agents, with a lean senior team directing and reviewing their work. You get:

  • Maximum of your budget working on the build, not on headcount
  • Working software at the end of every short sprint
  • A preview of what each change touches before it’s built
  • Sign-off on every release against standards agreed before coding starts

Engagement options

From idea validation to full-scale launch

  1. 01

    AI Agent Discovery

    1–2 weeks

    Validate the idea, scope, and architecture. Leave with a plan you can use with or without us, and an honest estimate.

    Best for: new ideas and unclear scope

  2. 02

    Proof of concept

    2–4 weeks

    Test technical risk on your real stack and data, not a demo dataset, before you commit to a bigger build.

    Best for: proving feasibility first

  3. 03

    MVP launch

    1–3 months

    Ship core functionality fast. Key user flows are demonstrated live on the real product, and you sign off before release.

    Best for: getting to real users quickly

  4. 04

    Full product

    1–4 months

    A complete, scalable product built for the long run, delivered with its plan, decision log, and audit-ready records.

    Best for: long-term and regulated builds

Our clients’ success stories

Let’s build something
great together.

Frequently Asked Questions

Production-grade, and we say so when a prototype is all you need. Every project runs on Production-Ready AI Engineering: a living plan with a check on every save, senior review on every design, and a person watching the product work before release.

Anthropic, OpenAI, Google Gemini, Mistral, Qwen, and open-weight models, chosen per use case on cost, latency, and risk. Our plan and checks do not depend on any one model, so we move to better ones as they arrive.

Yes. We add the plan beside your existing code without touching it, and the checks apply to new work from day one. Integrations run inside your CRM, ERP, data platform, and communication stack rather than beside them.

Discovery is a fixed two-week scope, quoted after a free 30-minute call. Build work runs as Dedicated Team or Agent-Led Delivery, with a range rather than a single number and the open questions that make the range wide named up front.

Senior engineers direct more than 100 AI agents that write the code and tests, review each other's work, and keep the plan current, around the clock, on our own platform built on Claude Code and OpenAI Codex. You decide what gets built; the agents do the typing.

They go into the plan first. Your requirements, whether SOC 2, HIPAA, PCI DSS, or your own policies, become rules every agent reads before it starts and the checker enforces on every change, including which models may see your code and what data the agents can touch.