AI consultancies win the brief on strategy, evaluation, and prompt design. AgencyRelay slots underneath as the production engineering layer — agents with evals and guardrails, RAG pipelines on real client data, and the integration depth that turns a working demo into a system the client trusts on a Monday morning.
These are the four moments most AI-led consultancies hit at least twice a year. AgencyRelay is built for exactly these — without you having to staff a full production engineering bench between roadmap engagements.
The notebook runs, the demo lands, the contract gets signed — and then the agent has to operate against real tools, real data, real users, and a real cost ceiling. Evals, guardrails, fallback paths, and observability stop being optional and become the entire engagement.
Strategy approved retrieval. Now someone has to own ingestion, chunking strategy, reranking, citation discipline, the eval harness, and the honest "I don't know" path — across a corpus that is bigger, messier, and more sensitive than any toy benchmark.
The discovery is done, the prioritisation is clean, the slide deck is signed off — and the client is asking for the first three roadmap items shipped this quarter. Without a real engineering layer, the consultancy that wrote the roadmap is the one that disappoints on it.
Audit logging, role-based access, per-tenant isolation, prompt-injection mitigations, model fallbacks, on-call ownership — these are the questions that move an AI engagement from "interesting pilot" to "line item the client renews". Most strategy-led consultancies do not staff for them.
Most AI consultancies start in Capability Expansion when the firm wants to carry AI implementation as a repeatable service line, or in Proposal Rescue Desk when an open AI bid needs a defensible technical scope. Invisible Delivery Team takes over once the engagement is steady-state production work.
Carry an entire AI service line — production agents, RAG, evals, and observability — under your brand without staffing the entire specialty in-house first. A named capability lead, paired with the engineering layer behind it.
A per-cycle technical pre-sales partner for the larger AI engagements. Solution direction, scope assumptions, an estimate range your account lead can defend on the call — and an honest read on what is doable inside the deadline.
Engineering pods that ship under your brand on the client's stack. The AI strategy stays with you — we sit behind it as the production layer at a steady weekly rhythm once the agent or pipeline is in real use.
These three carry the bulk of AI-consultancy engagements once the brief moves from strategy to shipped product. The full bench is broader — see the capability hub for AI workflow automation, integrations, web, backend, and ongoing-support depth.
End-to-end AI build — strategy and architecture across the four AI tracks, with the production engineering, evals, and observability that move a POC into a system the client trusts.
Production agents that take actions, call tools, and run multi-step workflows — with evals, guardrails, and a real fallback story when the model is wrong.
Retrieval-augmented generation built around the client's real content — chunking strategy, reranking, citation discipline, eval harness, and an honest "I don't know" path.
Most AI-consultancy engagements start with a Capability Expansion scoping call or a Proposal Rescue Desk cycle on an open bid. The first two weeks are deliberately slow — we'd rather map the data, the model, and the eval surface correctly than ship fast and have to unwind a brittle agent in production later.
60 minutes with the founder. We pull apart the consultancy model, the AI work you sell, the engagements you're not yet able to take, and the kind of production engineering AgencyRelay would carry. Mutual NDA before any client-specific brief, model, or data is shared.
One MSA with Salt Technologies, Inc. covers the relationship. The first SOW scopes a single engagement — usually one Capability Expansion scoping call or one Proposal Rescue Desk cycle on an open AI bid.
Named delivery lead, named AI engineer, model and tooling access, eval harness setup, and your project channel. Communication boundaries — and what we are or aren't allowed to do with the client's data — are agreed in writing before the first prompt runs.
Weekly check-ins with the delivery lead, founder review at agreed cadence, the same engineers on the engagement month-on-month. Evals run in CI, observability is live, capacity flexes by SOW amendment.
The most common shape for an AI consultancy is one Proposal Rescue Desk cycle on the larger AI bids, plus a Capability Expansion retainer when the AI implementation work becomes a repeatable service line. Both prices are public on the pricing page; the SOW is sized to the actual engagement.
Every engagement is contracted through Salt Technologies, Inc. The same operating principles apply across solutions and across the relationship — and the AI-specific guardrails sit on top of that.
We don't email your client, join their calls, or appear in the proposal — unless you explicitly white-list us in the SOW.
We don't approach your team and we don't accept introductions to your client off the back of an engagement.
Client prompts, evals, fine-tuning artefacts, and embeddings are not reused across engagements. Model and data access is scoped to the SOW and revoked on completion.
MSA, NDA, and SOWs are issued by Salt Technologies, Inc. — a 13+ year delivery company and the legal entity behind AgencyRelay.
The same operating principles apply across every solution and every engagement — including the Capability Expansion retainers and Proposal Rescue Desk cycles most AI consultancies start with.
Operational resources written for the same situations AI consultancies face — defending implementation scope at the bid stage, structuring a credible technical proposal for AI work, and selling more production-heavy engagements without over-hiring.
The internal playbook for triaging a wobbly AI proposal — what to ask, what to flag, how to defend the technical estimate when the client wants production agents, RAG, or integrations behind the strategy.
A reusable structure for the technical section of an AI-consultancy proposal — assumptions, risks, architecture, eval plan, estimate range — for agents, RAG, and complex AI integrations.
Why technical proposals lose late, and the moves AI-led founders use to make implementation scope defensible at the bid stage — without underselling the engineering work behind a strategy deck.
Direct answers to the questions that come up on almost every first call with an AI-led consultancy.
Not by default. Every engagement is white-label safe — we sit behind your team and the client only sees your brand. If you want a named technical lead joining a client call to talk through an evals plan or an architecture trade-off, we can do that, but it has to be explicitly white-listed in the SOW.
No. Strategy, evaluation direction, prompt design, and the client relationship all stay on your side. AgencyRelay carries the production engineering underneath — agents, RAG pipelines, evals, integrations, observability — so the strategy actually ships into a system the client trusts.
Yes. Production agents — tool use, multi-step workflows, evals running in CI, guardrails, prompt-injection mitigations, observability, and a real fallback story when the model is wrong — are common shapes inside Capability Expansion and Invisible Delivery Team. Larger ones usually start with a Proposal Rescue Desk cycle so the technical scope is defensible before the SOW is signed.
Yes. RAG & Knowledge AI is one of the three primary capabilities AI consultancies pull on. We own ingestion, chunking strategy, reranking, citation discipline, an eval harness, and the honest "I don't know" path. Embeddings and evals are not reused across engagements.
Model choice and evals direction stay with you — that's the strategy half of the engagement. We carry the eval harness, the regression tests, the prompt-injection mitigations, the per-tenant isolation, and the audit logging that move an AI engagement from interesting pilot to renewed line item. We do not publish model research on your behalf.
Proposal Rescue Desk is per-cycle, fixed price, no retainer. Capability Expansion is a monthly retainer when you're ready to carry AI implementation as a service line. The Solo Specialist pod inside Invisible Delivery Team starts weekly with no minimum number of weeks.
Once the partner call is done and the first SOW is signed, a Proposal Rescue Desk cycle can begin within 48 hours of NDA when there's a hard client deadline on an AI bid. Capability Expansion typically begins within 5–7 business days of the first SOW. Production engagements size onboarding around model and data access timelines.
Mutual NDA before any client-specific brief, model, or data is shared. Founder-led on every engagement. A clean read on whether the work is a fit — and which solution fits best — within the first call.
