AI-Native Agency vs the alternatives.

Traditional consulting sells frameworks, decks, and large teams billed by the hour. We sell scoped engagements that ship working AI workflows in production.

C-suite buyers evaluating a McKinsey, BCG, Accenture, or boutique digital practice for an AI transformation project

In-house wins when you have AI engineering capacity, labelled data, and a product manager dedicated to the workflow. Otherwise, an AI-native agency ships faster and cheaper.

Engineering leaders deciding whether to hire AI engineers internally or work with an AI-native agency for a specific workflow

SaaS AI platforms (ChatGPT Enterprise, Copilot, Glean) are great at horizontal productivity. They fail at workflow-specific accuracy, deep system integration, and measurable KPI lift.

Operations or IT leaders deciding between deploying a horizontal AI platform across the team or investing in a workflow-specific build

Freelancers are great for narrow technical tasks. They fail at workflow design, governance, and the operating discipline that makes AI workflows survive production past month three.

Operations or product leaders evaluating an Upwork-style freelance AI engineer vs a productized AI-native agency engagement

Scale AI is purpose-built for enterprise data labelling at scale and Fortune-100 GenAI deployments. We're built for mid-market AI workflow delivery with senior-level engineering at a fraction of the burn.

Mid-market AI buyer ($50M-$500M revenue) evaluating Scale AI's GenAI Platform for a workflow project

Palantir Foundry is an integrated data + AI platform optimised for large-scale, multi-source enterprise deployments. We're a delivery partner that ships AI workflows on top of your existing stack without requiring a platform commitment.

Mid-market or upper-mid-market buyer evaluating Foundry deployment for an AI/data workflow

Cognizant's AI practice is a large-team systems-integrator engagement. We're built for productized, fixed-price, fast-shipping AI workflow delivery.

Mid-market buyer evaluating Cognizant's AI practice for an enterprise workflow

Deloitte sells AI strategy and transformation programs. We ship working AI workflows on a fixed-price schedule. Different value, different price point.

C-suite buyer considering Deloitte for an AI transformation

Accenture Applied Intelligence is a large-scale AI systems integrator. We're built for mid-market AI workflow delivery without large-team economics.

Mid-market buyer evaluating Accenture for an AI deployment

Galileo is an LLM evaluation and observability platform. We're a delivery partner who'll set up Galileo (or alternatives) as part of your workflow's eval harness.

AI engineering team evaluating LLM eval/observability platforms

Cresta is a contact-center AI product. We build custom AI workflows when the off-the-shelf product doesn't fit your specific operating model.

Contact-center or customer-ops leader evaluating Cresta's AI platform

Decagon ships AI customer-service agents as a managed product. We build custom AI workflows when your operating model is non-standard.

Customer experience leader evaluating Decagon for AI agents

Sierra is a high-end AI customer-experience platform optimised for consumer brands. We build custom AI workflows for B2B and regulated buyers Sierra's product shape doesn't cover.

CX leader at consumer-facing brand evaluating Sierra's AI agent platform

Glean is the leading enterprise search and AI knowledge platform. We build custom AI workflows on top of (or in parallel to) Glean for specific use cases.

Enterprise buyer evaluating Glean for enterprise search + AI knowledge

Hebbia is a high-end AI document analysis platform for financial services, legal, and consulting. We build custom workflows when the product shape doesn't fit.

Financial services / legal / consulting buyer evaluating Hebbia for document analysis at scale

Harvey is a top-tier legal AI platform for AmLaw firms and in-house legal. We build custom legal workflows when the platform doesn't fit (regional bar regulations, custom playbooks, non-AmLaw firms).

Law firm or in-house legal leader evaluating Harvey for legal AI workflows

Both are excellent. We pick per labelled test set, not per leaderboard. In mid-2026, Claude tends to win on cost/quality for routine workflow tasks; GPT-4 wins on multimodal and tool-use depth.

AI engineering or platform leader choosing between Claude and GPT-4 for production workflows

Build in-house when AI is your competitive moat. Engage an agency when you need an AI workflow in production fast and AI engineering isn't your core differentiator.

CTO/CIO deciding whether to hire 3-5 AI engineers or engage an AI-native agency