The AI agency that ships products, not slide decks
Swfte is a full-stack AI agency. We design the strategy, build the agents, ship them on a managed runtime your team keeps, and stay on as the program scales. From the first 2-week discovery sprint to a 12-month managed AI program. Strategy → build → run, all on one platform.
What an AI agency engagement covers in 2026
Six service lines, all aligned with a single managed runtime so handovers are clean and the production system is the artifact, not a slide deck.
AI strategy and roadmap
Quarterly executive workshops that turn an AI ambition into a 6-12 month roadmap with named workloads, named owners, named KPIs. Anchored against your existing tech stack, regulatory posture, and capacity. Output: a written roadmap your CFO can fund and your CISO can sign.
AI agent build + deploy
Custom AI agents for customer support, internal IT, sales operations, document processing, and developer productivity. Built on Swfte's managed runtime so the org keeps the gateway, eval harness, and per-team cost ceilings after the engagement ends. Typical first-agent delivery: 4-6 weeks from kickoff.
LLM cost optimisation
Audit of existing LLM spend with a routing + caching + batching plan. The standard outcome is a 40-80% reduction in model spend without measurable quality loss, achieved by routing 70-80% of requests to a smaller tier and applying provider-native prompt caching (90% off on Anthropic and DeepSeek, 75% off on OpenAI and Gemini).
Eval + governance harness
A production eval harness on top of your gateway. golden datasets, LLM-as-judge, shadow A/B between providers, regression UI, and a governance report your audit committee can read. The same harness powers per-team SLOs and incident triage.
AI compliance program
Build a procurement-grade AI program: NIST AI RMF mapping, EU AI Act conformity preparation, ISO/IEC 42001 alignment, and per-model risk scorecards. Output is an audit-ready binder, not a slide deck.
Workforce enablement
Role-based AI training for non-technical staff (operations, sales, support, finance), with playbooks and graded competency exits. Pairs with Swfte's UpSkill product for org-wide rollout.
Engagement models
Four packaged engagement shapes covering everything from a 2-week exploratory sprint to a 12-month managed AI program. Most enterprises start with a Pilot Build and graduate into Fleet Rollout within two quarters.
| Engagement | Duration | Deliverable | Right fit |
|---|---|---|---|
| Discovery sprint | 2 weeks | Written AI opportunity report + prioritised backlog | CTOs exploring "what could AI do for us?" |
| Pilot build | 4-6 weeks | One production AI agent + handover docs | Teams with a known target workload |
| Fleet rollout | 3-6 months | 3-10 production AI agents on Swfte runtime | Orgs scaling AI org-wide |
| Managed AI program | 12+ months | Ongoing AI strategy + delivery + governance | Enterprises building a long-term AI capability |
Industry-specific patterns
Six industry verticals where we have deep production patterns and compliance posture. Each comes with a starter set of agent templates, reference architectures, and the governance documentation your auditors will ask for.
Financial services
Customer support agents grounded in policy documents, AI-assisted KYC and document processing, AI underwriting copilots, and AI compliance monitoring agents. All on a SOC2 + on-prem / VPC posture acceptable to risk and compliance.
Healthcare
HIPAA-aligned agents for patient communication, clinical documentation assistance, prior authorisation, and revenue cycle. Provider routing favours models with zero data retention and on-prem deployment paths.
Legal
Document review, case research, contract analysis, and discovery agents grounded in proprietary corpora. Citation-grounded retrieval pattern keeps every answer source-attributable for partner review.
Manufacturing + supply chain
AI agents for supplier onboarding, purchase order processing, returns management, and field service. Strong fit for the cost-attribution primitives that show return per agent per quarter.
Public sector
Constituent-facing intake agents, internal knowledge agents, FOIA / records processing, and EU AI Act conformity programmes. On-prem + air-gapped deployment options available.
Technology + SaaS
Developer productivity (Cursor + Claude Code fleets), customer support copilots, embedded AI inside the SaaS product, and AI sales operations. Self-serve onboarding to the gateway in days.
Why most AI agencies disappoint: and how Swfte is structured to avoid it
The standard AI agency engagement in 2023-24 produced a polished prototype and a written report. The prototype rarely reached production because the agency owned the stack, the prompts, the model accounts, and the operational scaffolding. When the engagement ended, the org was left with a deck and a Slack channel of vendor relationships. That is not a working AI program.
Swfte is structured around a different default; every deliverable ships on a managed runtime the customer owns. The gateway, agent definitions, eval datasets, per-team budgets, audit logs, and observability traces are all in the customer's account from day one. The agency role is to accelerate, not to gatekeep. When the engagement ends, the customer has a working product and an operational manual, not a slide deck.
That structure is also why our retainer rates are competitive with traditional consultancies, and we are not double-charging for hosted infrastructure. The runtime is the same one the customer would have bought directly; the agency layer is genuinely additive.
FAQ
What is an AI agency?
An AI agency is a professional services firm that designs, builds, and deploys AI systems, chatbots, agents, copilots, automation pipelines, and decision support: for organisations that prefer to buy outcomes rather than hire an internal AI team. The best AI agencies operate as an extension of your engineering, with handover docs and a runtime the org keeps after the engagement.
How much does an AI agency cost in 2026?
A 2-week discovery sprint ranges from $25,000 to $60,000. A 4-6 week pilot agent build ranges from $80,000 to $250,000 depending on complexity. A 3-6 month fleet rollout typically lands between $250,000 and $1.5M. Ongoing managed AI programs are usually monthly retainer plus model spend. Swfte's engagements include the production runtime, so there is no separate infrastructure invoice.
How do you measure ROI on an AI agency engagement?
Per-agent. Each agent ships with a defined KPI (tickets resolved per hour, documents processed per minute, lead-to-meeting conversion rate, code review throughput) and a cost-per-task ceiling enforced at the gateway. The standard reporting cadence is monthly per-team return-on-tokens, plus a quarterly executive review.
What makes Swfte different from other AI agencies?
Most agencies bill for a deliverable and leave. Swfte ships the deliverable on a managed runtime; gateway, agent orchestration, eval, observability, per-team cost ceilings, SOC2 posture, and that the org keeps. The handover is to a working product, not a slide deck. The runtime is provider-portable: Claude, GPT, Gemini, DeepSeek, Grok, Llama, and self-hosted endpoints behind one policy plane.
How long until we see results from an AI agency engagement?
First measurable result inside 30 days from the pilot build kickoff. The first production agent typically reaches a useful KPI by week 4-6 with a 90-day ramp to steady state. Fleet rollouts begin showing aggregate org-wide ROI by month 3.
Do AI agencies work for small businesses, or only enterprise?
Both. Swfte's SMB program packages a 2-week discovery + 1 production agent inside a fixed-fee envelope under $50,000. Enterprise programs are scoped per engagement. The underlying runtime is the same. so an SMB pilot upgrades to a fleet rollout without re-platforming.
What is the difference between an AI agency and an AI consultancy?
An AI consultancy advises. An AI agency advises and builds. The line has blurred since 2024, most modern AI agencies cover strategy, build, and managed run. The right partner for most teams is the one that can do all three on one runtime so handovers are clean.
Which AI models does an AI agency typically use?
In 2026, a typical AI agency engagement settles on Claude Opus 4.7 or Sonnet 4 for code and agentic workloads, GPT-5.5 for voice and reasoning, Gemini 3.0 for cost-sensitive bulk traffic, DeepSeek V4 Pro for sovereignty-sensitive workloads, and Grok 4 only when real-time X data is part of the input. All routed through one gateway with policy-driven fallback.
How do AI agencies handle data privacy?
Through three primitives: provider-side zero data retention (default on Anthropic paid contracts, available on OpenAI, Gemini, DeepSeek enterprise), gateway-level audit logs, and on-prem / VPC deployment for the gateway itself. For regulated workloads, the entire runtime can be deployed inside your network with no traffic leaving the perimeter.
Do I need an AI agency if I already have engineers?
Maybe not: depends on capacity, expertise, and timeline. Engineering teams that have already shipped two or three production AI agents usually have the muscle to keep going. Teams that are stuck on the first agent, or that have a regulatory or governance gap, get a meaningful acceleration from an agency engagement.
Ready to ship AI agents that actually move the needle?
Swfte runs the strategy, build, and operations on one managed runtime. Strategy → build → run.
Free tier · OpenAI-compatible API · SOC2 Type II · On-prem available